阅读说明：本技术 一种高频地波雷达一阶峰信噪比阈值确定方法及系统 (Method and system for determining first-order peak signal-to-noise ratio threshold of high-frequency ground wave radar ) 是由 沈伟 徐满 于 2021-11-17 设计创作，主要内容包括：本发明实施例公开了一种高频地波雷达一阶峰信噪比阈值确定方法,包括：根据历史雷达采样数据的雷达回波信号能量和噪声能量数据,生成以时刻和距离元为索引的信噪比阈值查找表,以时刻和距离元为索引的信噪比阈值查找表包括多个时刻,每个时刻包括各个距离元对应的信噪比阈值；根据雷达实际的工作时间和实际的距离元,从以时刻和距离元为索引的信噪比阈值查找表中提取与实际的工作时间和实际的距离元对应的信噪比阈值。本发明实施例还公开了一种高频地波雷达一阶峰信噪比阈值确定系统。本发明将探测海域环境因素纳入信噪比阈值中,得到的信噪比阈值更符合信号和噪声实际变化规律,增强了信噪比阈值与网格单元的相关性,提高了一阶峰判断的准确程度。(The embodiment of the invention discloses a method for determining a first-order peak signal-to-noise ratio threshold of a high-frequency ground wave radar, which comprises the following steps: generating a signal-to-noise ratio threshold lookup table with time and distance elements as indexes according to radar echo signal energy and noise energy data of historical radar sampling data, wherein the signal-to-noise ratio threshold lookup table with the time and the distance elements as indexes comprises a plurality of times, and each time comprises a signal-to-noise ratio threshold corresponding to each distance element; and extracting the signal-to-noise ratio threshold corresponding to the actual working time and the actual distance element from the signal-to-noise ratio threshold lookup table taking the time and the distance element as indexes according to the actual working time and the actual distance element of the radar. The embodiment of the invention also discloses a system for determining the first-order peak signal-to-noise ratio threshold of the high-frequency ground wave radar. The invention brings the environmental factors of the detected sea area into the threshold value of the signal-to-noise ratio, the obtained threshold value of the signal-to-noise ratio is more in line with the actual change rule of the signal and the noise, the correlation between the threshold value of the signal-to-noise ratio and the grid unit is enhanced, and the accuracy of the first-order peak judgment is improved.)

1. A method for determining a first-order peak signal-to-noise ratio threshold of a high-frequency ground wave radar is characterized by comprising the following steps:

s1, generating a signal-to-noise ratio threshold lookup table with time and distance elements as indexes according to radar echo signal energy and noise energy data of historical radar sampling data in a preset time period, wherein the signal-to-noise ratio threshold lookup table with the time and the distance elements as indexes comprises a plurality of times, and each time comprises a signal-to-noise ratio threshold corresponding to each distance element;

and S2, extracting the SNR threshold corresponding to the actual working time and the actual distance element from the SNR threshold lookup table with the time and the distance element as indexes according to the actual working time and the actual distance element of the radar.

2. The method of claim 1, wherein the historical radar sample data over the preset time period comprises a plurality of days of radar sample data, the daily radar sample data comprising a plurality of fields of data, the S1 comprising:

s11, processing the actual signal power and the actual noise power of each distance element for one field of data every day to obtain the signal-to-noise ratio corresponding to each distance element;

s12, obtaining a first signal-to-noise ratio threshold lookup table based on signal-to-noise ratios corresponding to distance elements of multi-field data in each day, wherein the first signal-to-noise ratio threshold lookup table comprises a plurality of moments in each day, and each moment comprises the signal-to-noise ratio corresponding to each distance element;

s13, according to the preset time number, time completion is carried out on the first signal-to-noise ratio threshold lookup table to obtain a second signal-to-noise ratio threshold lookup table;

s14, extracting elements at the same position in each second SNR threshold lookup table in a preset time period to form a sequence table, wherein the same position represents the SNR corresponding to the same distance element at the same time, the sequence table comprises a plurality of times, and each time comprises the SNR corresponding to the same distance element on each day;

and S15, processing the signal-to-noise ratio corresponding to the same distance element on each day at each moment in the sequence list to obtain the signal-to-noise ratio threshold corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold lookup table with the moment and the distance elements as indexes.

3. The method of claim 2, wherein the S11 includes:

s111, extracting signal energy and noise energy of all distance elements from one field of data every day to obtain a signal energy and noise energy list, wherein the signal energy and noise energy list comprises a plurality of frequency points, and each frequency point comprises actual signal power and actual noise power corresponding to each distance element;

s112, determining the mean value of the actual signal power of all the frequency points and the variance between the actual signal power of each frequency point and the mean value for each distance element based on the signal energy and noise energy list, and taking the actual signal power of the frequency point corresponding to the minimum variance value as the signal power of the distance element to obtain the signal power of all the distance elements;

determining the average value of the actual noise power of the frequency points on two sides in all the frequency points for each distance element based on the signal energy and noise energy list, and taking the average value as the noise power of the distance element to obtain the noise power of all the distance elements, wherein the number of the frequency points on two sides is 1/4 of the number of all the frequency points;

s113, obtaining a signal-to-noise ratio corresponding to each distance element based on the signal power of each distance element and the noise power of each distance element.

4. The method of claim 2, wherein in S13, when time-filling the first SNR threshold lookup table,

and the signal-to-noise ratios corresponding to the distance elements at the lacking moment are obtained by performing interpolation calculation on the signal-to-noise ratios corresponding to the distance elements at the moments before and after the lacking moment.

5. The method of claim 2, wherein the S15 includes:

s151, determining the mean value and the median value of the signal-to-noise ratio for all the signal-to-noise ratios in the current moment in the sequence table;

s152, in the sequence table, for each signal-to-noise ratio at the current moment, determining a first difference between the signal-to-noise ratio and the mean value of the signal-to-noise ratio and a second difference between the signal-to-noise ratio and the median value of the signal-to-noise ratio to obtain the sum of absolute values of the first difference and the second difference;

s153, regarding the current distance element at the current moment in the sequence table, taking the signal-to-noise ratio corresponding to the minimum value of the sum of absolute values as the signal-to-noise ratio threshold value corresponding to the current distance element at the current moment;

s154, repeating S151-S153 for each distance element at each moment in the sequence table to obtain the signal-to-noise ratio threshold corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold lookup table with the moment and the distance elements as indexes.

6. The method of claim 1, wherein the S2 includes:

s21, actual working time by radarThe starting time of the SNR threshold lookup table with the time and the distance element as indexesAnd time interval of radar samplingObtaining a time index；

S22, obtaining a distance element index according to the difference between the actual distance element and the initial distance element;

and S23, extracting the SNR threshold corresponding to the time index and the distance element from the SNR threshold lookup table using the time and the distance element as indexes.

7. A high frequency ground wave radar first order peak signal to noise ratio threshold determination system, the system comprising:

the signal-to-noise ratio threshold lookup table determining module is used for generating a signal-to-noise ratio threshold lookup table with time and distance elements as indexes according to radar echo signal energy and noise energy data of historical radar sampling data in a preset time period, wherein the signal-to-noise ratio threshold lookup table with the time and the distance elements as indexes comprises a plurality of times, and each time comprises a signal-to-noise ratio threshold corresponding to each distance element;

and the signal-to-noise ratio threshold extraction module is used for extracting the signal-to-noise ratio threshold corresponding to the actual working time and the actual distance element from the signal-to-noise ratio threshold lookup table which takes the moment and the distance element as indexes according to the actual working time and the actual distance element of the radar.

8. An electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method of any of claims 1-6.

9. A computer-readable storage medium, on which a computer program is stored, the computer program being executable by a processor for implementing the method according to any one of claims 1-6.

Technical Field

The invention relates to the technical field of radars, in particular to a method and a system for determining a first-order peak signal-to-noise ratio threshold of a high-frequency ground wave radar.

Background

At present, the method for determining the first-order peak signal-to-noise ratio threshold of the high-frequency ground wave radar mainly comprises the following steps: the method comprises the steps of full-range step constant value, sub-range step constant value and sub-range step and linear combination, and the determination methods are all based on signal-to-noise ratio threshold values obtained through linear calculation. The attenuation curve of the energy propagated by the high-frequency electromagnetic wave along the sea surface is similar to a high-order exponential curve, so that the signal-to-noise ratio threshold obtained by the method through linear calculation is not suitable and cannot reasonably correspond to the change of the signal-to-noise ratio in the frequency band.

Disclosure of Invention

In order to solve the above problems, an object of the present invention is to provide a method and a system for determining a first-order peak snr threshold of a high-frequency ground wave radar, wherein a detected sea area environmental factor is incorporated into the snr threshold, and the obtained snr threshold better conforms to an actual change rule of a signal and noise, thereby enhancing a correlation between the snr threshold and a grid unit and improving an accuracy of first-order peak determination.

The embodiment of the invention provides a method for determining a first-order peak signal-to-noise ratio threshold of a high-frequency ground wave radar, which comprises the following steps:

s1, generating a signal-to-noise ratio threshold lookup table with time and distance elements as indexes according to radar echo signal energy and noise energy data of historical radar sampling data in a preset time period, wherein the signal-to-noise ratio threshold lookup table with the time and the distance elements as indexes comprises a plurality of times, and each time comprises a signal-to-noise ratio threshold corresponding to each distance element;

and S2, extracting the SNR threshold corresponding to the actual working time and the actual distance element from the SNR threshold lookup table with the time and the distance element as indexes according to the actual working time and the actual distance element of the radar.

As a further improvement of the present invention, the historical radar sample data in the preset time period includes radar sample data of multiple days, the radar sample data of each day includes multi-field data, and the S1 includes:

s11, processing the actual signal power and the actual noise power of each distance element for one field of data every day to obtain the signal-to-noise ratio corresponding to each distance element;

s12, obtaining a first signal-to-noise ratio threshold lookup table based on signal-to-noise ratios corresponding to distance elements of multi-field data in each day, wherein the first signal-to-noise ratio threshold lookup table comprises a plurality of moments in each day, and each moment comprises the signal-to-noise ratio corresponding to each distance element;

s13, according to the preset time number, time completion is carried out on the first signal-to-noise ratio threshold lookup table to obtain a second signal-to-noise ratio threshold lookup table;

s14, extracting elements at the same position in each second SNR threshold lookup table in a preset time period to form a sequence table, wherein the same position represents the SNR corresponding to the same distance element at the same time, the sequence table comprises a plurality of times, and each time comprises the SNR corresponding to the same distance element on each day;

and S15, processing the signal-to-noise ratio corresponding to the same distance element on each day at each moment in the sequence list to obtain the signal-to-noise ratio threshold corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold lookup table with the moment and the distance elements as indexes.

As a further improvement of the present invention, said S11 includes:

s111, extracting signal energy and noise energy of all distance elements from one field of data every day to obtain a signal energy and noise energy list, wherein the signal energy and noise energy list comprises a plurality of frequency points, and each frequency point comprises actual signal power and actual noise power corresponding to each distance element;

s112, determining the mean value of the actual signal power of all the frequency points and the variance between the actual signal power of each frequency point and the mean value for each distance element based on the signal energy and noise energy list, and taking the actual signal power of the frequency point corresponding to the minimum variance value as the signal power of the distance element to obtain the signal power of all the distance elements;

determining the average value of the actual noise power of the frequency points on two sides in all the frequency points for each distance element based on the signal energy and noise energy list, and taking the average value as the noise power of the distance element to obtain the noise power of all the distance elements, wherein the number of the frequency points on two sides is 1/4 of the number of all the frequency points;

s113, obtaining a signal-to-noise ratio corresponding to each distance element based on the signal power of each distance element and the noise power of each distance element.

As a further improvement of the present invention, in S13, when the first snr threshold lookup table is time-padded,

and the signal-to-noise ratios corresponding to the distance elements at the lacking moment are obtained by performing interpolation calculation on the signal-to-noise ratios corresponding to the distance elements at the moments before and after the lacking moment.

As a further improvement of the present invention, said S15 includes:

s151, determining the mean value and the median value of the signal-to-noise ratio for all the signal-to-noise ratios in the current moment in the sequence table;

s152, in the sequence table, for each signal-to-noise ratio at the current moment, determining a first difference between the signal-to-noise ratio and the mean value of the signal-to-noise ratio and a second difference between the signal-to-noise ratio and the median value of the signal-to-noise ratio to obtain the sum of absolute values of the first difference and the second difference;

s153, regarding the current distance element at the current moment in the sequence table, taking the signal-to-noise ratio corresponding to the minimum value of the sum of absolute values as the signal-to-noise ratio threshold value corresponding to the current distance element at the current moment;

s154, repeating S151-S153 for each distance element at each moment in the sequence table to obtain the signal-to-noise ratio threshold corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold lookup table with the moment and the distance elements as indexes.

As a further improvement of the present invention, said S2 includes:

s21, actual working time by radarThe starting time of the SNR threshold lookup table with the time and the distance element as indexesAnd time interval of radar samplingObtaining a time index；

S22, obtaining a distance element index according to the difference between the actual distance element and the initial distance element;

and S23, extracting the SNR threshold corresponding to the time index and the distance element from the SNR threshold lookup table using the time and the distance element as indexes.

The embodiment of the invention also provides a system for determining the first-order peak signal-to-noise ratio threshold of the high-frequency ground wave radar, which comprises the following steps:

the signal-to-noise ratio threshold lookup table determining module is used for generating a signal-to-noise ratio threshold lookup table with time and distance elements as indexes according to radar echo signal energy and noise energy data of historical radar sampling data in a preset time period, wherein the signal-to-noise ratio threshold lookup table with the time and the distance elements as indexes comprises a plurality of times, and each time comprises a signal-to-noise ratio threshold corresponding to each distance element;

and the signal-to-noise ratio threshold extraction module is used for extracting the signal-to-noise ratio threshold corresponding to the actual working time and the actual distance element from the signal-to-noise ratio threshold lookup table which takes the moment and the distance element as indexes according to the actual working time and the actual distance element of the radar.

As a further improvement of the present invention, the snr threshold lookup table determining module includes:

processing the actual signal power and the actual noise power of each distance element for one field of data in each day to obtain the signal-to-noise ratio corresponding to each distance element;

obtaining a first signal-to-noise ratio threshold lookup table based on signal-to-noise ratios corresponding to distance elements of multiple fields of data every day, wherein the first signal-to-noise ratio threshold lookup table comprises multiple moments in a day, and each moment comprises the signal-to-noise ratio corresponding to each distance element;

according to the preset time number, time completion is carried out on the first signal-to-noise ratio threshold lookup table to obtain a second signal-to-noise ratio threshold lookup table;

extracting elements at the same position in each second signal-to-noise ratio threshold lookup table in a preset time period to form a sequence table, wherein the same position represents the signal-to-noise ratio corresponding to the same distance element at the same time, the sequence table comprises a plurality of times, and each time comprises the signal-to-noise ratio corresponding to the same distance element at each day;

and processing the signal-to-noise ratio corresponding to the same distance element on each day at each moment in the sequence list to obtain the signal-to-noise ratio threshold value corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold value lookup table with the moment and the distance elements as indexes.

As a further improvement of the present invention, the processing the actual signal power and the actual noise power of each distance element for one field of data in each day to obtain the signal-to-noise ratio corresponding to each distance element includes:

extracting signal energy and noise energy of all distance elements from one field of data every day to obtain a signal energy and noise energy list, wherein the signal energy and noise energy list comprises a plurality of frequency points, and each frequency point comprises actual signal power and actual noise power corresponding to each distance element;

determining the mean value of the actual signal power of all the frequency points and the variance between the actual signal power of each frequency point and the mean value for each distance element based on the signal energy and noise energy list, and taking the actual signal power of the frequency point corresponding to the minimum variance value as the signal power of the distance element to obtain the signal power of all the distance elements; determining the average value of the actual noise power of the frequency points on two sides in all the frequency points for each distance element based on the signal energy and noise energy list, and taking the average value as the noise power of the distance element to obtain the noise power of all the distance elements, wherein the number of the frequency points on two sides is 1/4 of the number of all the frequency points;

and obtaining the signal-to-noise ratio corresponding to each distance element based on the signal power of each distance element and the noise power of each distance element.

As a further improvement of the present invention, in time-filling the first snr threshold lookup table,

and the signal-to-noise ratios corresponding to the distance elements at the lacking moment are obtained by performing interpolation calculation on the signal-to-noise ratios corresponding to the distance elements at the moments before and after the lacking moment.

As a further improvement of the present invention, in the sequence table, the processing the snr corresponding to the same distance element on each day at each time to obtain the snr threshold corresponding to each distance element at each time, and generating the snr threshold lookup table using the time and the distance element as an index includes:

in the sequence table, determining the mean value and the median value of the signal-to-noise ratios of all the signal-to-noise ratios at the current moment;

in the sequence table, for each signal-to-noise ratio at the current moment, determining a first difference between the signal-to-noise ratio and the mean value of the signal-to-noise ratio and a second difference between the signal-to-noise ratio and the median value of the signal-to-noise ratio to obtain the sum of absolute values of the first difference and the second difference;

in the sequence table, for the current distance element at the current moment, taking the signal-to-noise ratio corresponding to the minimum value of the sum of absolute values as the signal-to-noise ratio threshold value corresponding to the current distance element at the current moment;

and repeating the steps for each distance element at each moment in the sequence table to obtain the signal-to-noise ratio threshold corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold lookup table with the moment and the distance elements as indexes.

As a further improvement of the present invention, the signal-to-noise ratio threshold extraction module comprises:

by actual operating time of the radarThe starting time of the SNR threshold lookup table with the time and the distance element as indexesAnd time interval of radar samplingObtaining a time index；

Obtaining a distance element index according to the difference between the actual distance element and the initial distance element;

and extracting the signal-to-noise ratio threshold value corresponding to the time index and the distance element from the signal-to-noise ratio threshold value lookup table taking the time and the distance element as indexes.

Embodiments of the present invention also provide an electronic device, which includes a memory and a processor, where the memory is configured to store one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the method.

Embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, the computer program being executed by a processor to implement the method.

The invention has the beneficial effects that:

the method comprises the steps of generating a signal-to-noise ratio threshold lookup table by using actual radar echo signal energy and noise energy data and taking time and distance as indexes, wherein the lookup table brings the salinity, water temperature, water depth, day and night signal energy attenuation and other factor environments of a detected sea area into the signal-to-noise ratio threshold, so that the signal-to-noise ratio threshold is as close to the change rule of signals and noise as possible, effective signals are more effectively reserved, the noise is suppressed, the obtained signal-to-noise ratio threshold is more in line with the actual change rule of the signals and the noise, the correlation between the signal-to-noise ratio threshold and grid units is enhanced, and the accuracy of first-order peak judgment is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.

Fig. 1 is a schematic flow chart of a method for determining a first-order peak snr threshold of a high-frequency ground wave radar according to an exemplary embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that, if directional indications (such as up, down, left, right, front, and back … …) are involved in the embodiment of the present invention, the directional indications are only used to explain the relative positional relationship between the components, the movement situation, and the like in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indications are changed accordingly.

In addition, in the description of the present invention, the terms used are for illustrative purposes only and are not intended to limit the scope of the present invention. The terms "comprises" and/or "comprising" are used to specify the presence of stated elements, steps, operations, and/or components, but do not preclude the presence or addition of one or more other elements, steps, operations, and/or components. The terms "first," "second," and the like may be used to describe various elements, not necessarily order, and not necessarily limit the elements. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified. These terms are only used to distinguish one element from another. These and/or other aspects will become apparent to those of ordinary skill in the art in view of the following drawings, and the description of the embodiments of the present invention will be more readily understood by those of ordinary skill in the art. The drawings are only for purposes of illustrating the described embodiments of the invention. One skilled in the art will readily recognize from the following description that alternative embodiments of the structures and methods illustrated in the present application may be employed without departing from the principles described in the present application.

The method for determining the first-order peak signal-to-noise ratio threshold of the high-frequency ground wave radar in the embodiment of the invention is shown in figure 1 and comprises the following steps:

s1, generating a signal-to-noise ratio threshold lookup table with time and distance elements as indexes according to radar echo signal energy and noise energy data of historical radar sampling data in a preset time period, wherein the signal-to-noise ratio threshold lookup table with the time and the distance elements as indexes comprises a plurality of times, and each time comprises a signal-to-noise ratio threshold corresponding to each distance element;

and S2, extracting the SNR threshold corresponding to the actual working time and the actual distance element from the SNR threshold lookup table with the time and the distance element as indexes according to the actual working time and the actual distance element of the radar.

The high-frequency ground wave radar is an instrument for measuring the state of the surface of the sea by receiving electromagnetic wave signals reflected by the sea surface. Sea waves with the same wavelength on the sea surface have certain components in all directions under the influence of the space propagation characteristics of the sea waves, so that two rows of far and near sea waves meeting the Bragg scattering wavelength always exist in the radial direction of the radar at the same time. The echoes of the two trains of sea waves appear to have two strong spectral peaks in the echo doppler spectrum and are symmetrical. These two spectral peaks are referred to as first order peaks. The echo doppler shift of these two trains of waves depends on the phase velocity of the corresponding wave train. Because the ocean current has a transportation function on the ocean waves, the phase velocity of the ocean waves carried on the ocean current is the component superposition of the phase velocity of the ocean waves in the static water and the flow velocity of the ocean current in the advancing direction of the ocean waves. Therefore, the current flow velocity in the radial direction of the radar, i.e. the radial flow velocity, can be calculated according to the difference between the current phase velocity of the sea wave and the phase velocity of the sea wave in the absence of the sea current.

Under the condition of knowing the working frequency of the radar, the corresponding ocean current flow velocity can be calculated as long as the Doppler frequency shift of the echo of the ocean wave target can be measured. Before calculating the doppler frequency shift using the frequency points corresponding to the first-order peak, we need to determine whether the first-order peak can be used to extract the ocean current parameters. The judgment is based on whether the signal-to-noise ratio of the first-order peak energy exceeds the signal-to-noise ratio threshold.

The existing method for determining the first-order peak signal-to-noise ratio threshold of the high-frequency ground wave radar mainly comprises the following three methods:

1. full-distance segment constant value: and setting the signal-to-noise ratio threshold value as a fixed value within the range of the radar detection range.

2. Step fixed value of the distance division section: and respectively assigning a fixed signal-to-noise ratio threshold value to the areas smaller than and larger than the maximum detection distance by taking half of the maximum detection distance of the radar as a boundary.

3. Distance-segmented ladder and linear combination: dividing a radar detection area into three intervals according to radar detection distance, endowing fixed signal-to-noise ratio thresholds in the interval close to a radar station and the interval far away from the radar station, using a linear equation to realize dynamic adjustment of the signal-to-noise ratio thresholds along with the distance in the middle interval, and determining the distance upper limit and the distance lower limit of the middle area according to experience data to realize the division of the three intervals.

The ideal energy attenuation of the high-frequency electromagnetic wave propagating along the sea surface is not linearly attenuated along the distance, and the noise energy also has certain fluctuation in a frequency band. Therefore, the above three methods for determining the snr threshold cannot reasonably correspond to the snr variation in the frequency band. In a region where the actual signal-to-noise ratio drops rapidly, the signal-to-noise ratio threshold determined by the method is much larger than the actual signal-to-noise ratio, so that signals in the region are discarded, and the discarded signals include both noise signals and echo signals which are attenuated too much due to sea conditions. In a region where the actual signal-to-noise ratio changes slowly, the signal-to-noise ratio threshold determined by the method is far smaller than the actual signal-to-noise ratio, so that some noise signals can be mistakenly considered as valid signals to be extracted, and a lot of ocean current data which are actually noise appear in a final result.

The theoretical attenuation curve of the energy propagated by the high-frequency electromagnetic wave along the sea surface is similar to a high-order exponential curve, so that the signal-to-noise ratio threshold obtained by the method through linear calculation is not applicable. Even if a high-order exponential equation is used for fitting the energy attenuation curve, since the echo energy attenuation is also influenced by environmental factors such as salinity and water depth of the measured sea area, the signal-to-noise ratio threshold value obtained by fitting the curve cannot meet the actual change rule of signals and noise, and the fitted signal-to-noise ratio threshold value still needs to be corrected according to the actual environment of the measured sea area.

The method calculates the SNR threshold value according to the measured radar data (historical radar sampling data in a preset time period), because the measured data brings the influence of factors such as salinity, water temperature, water depth and radar channel state of a detected sea area on signal energy into the SNR threshold value, compared with the SNR threshold value obtained by a step-type SNR threshold value and an interval SNR threshold value linear adjustment method, the obtained SNR threshold value better accords with the change rule of signal and noise energy under the actual condition, and better accords with the current condition of radar equipment and the actual condition of the radar detected sea area.

The method of the invention adopts a method of searching a signal-to-noise ratio threshold lookup table to determine the threshold corresponding to the actual working time and the distance element, and compared with a theoretical curve fitting mode, the method of the invention can obtain the signal-to-noise ratio threshold result more quickly and simply in the actual use process than a calculation equation. And the SNR threshold lookup table takes the radar single field data time and the radar detection range element as indexes, so that the SNR threshold corresponds to the radar data time and each range element, the process of determining the signal attenuation jump time point is omitted, the correlation between the corresponding SNR threshold and the radar signal energy change is improved, meanwhile, the SNR threshold does not need to be additionally processed in time and space, and the overall efficiency of the SNR threshold determination process is improved.

In an optional embodiment, the historical radar sample data in the preset time period includes radar sample data of multiple days, the radar sample data of each day includes multi-field data, and the S1 includes:

s11, processing the actual signal power and the actual noise power of each distance element for one field of data every day to obtain the signal-to-noise ratio corresponding to each distance element;

s12, obtaining a first signal-to-noise ratio threshold lookup table based on signal-to-noise ratios corresponding to distance elements of multi-field data in each day, wherein the first signal-to-noise ratio threshold lookup table comprises a plurality of moments in each day, and each moment comprises the signal-to-noise ratio corresponding to each distance element;

s13, according to the preset time number, time completion is carried out on the first signal-to-noise ratio threshold lookup table to obtain a second signal-to-noise ratio threshold lookup table;

s14, extracting elements at the same position in each second SNR threshold lookup table in a preset time period to form a sequence table, wherein the same position represents the SNR corresponding to the same distance element at the same time, the sequence table comprises a plurality of times, and each time comprises the SNR corresponding to the same distance element on each day;

and S15, processing the signal-to-noise ratio corresponding to the same distance element on each day at each moment in the sequence list to obtain the signal-to-noise ratio threshold corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold lookup table with the moment and the distance elements as indexes.

It is understood that the method of the present invention performs spatial and temporal processing on the snr threshold, the steps S11-S13 can be understood as snr threshold spatial processing, and the steps S14-S15 can be understood as snr threshold temporal processing. One field of data corresponds to one acquisition time period, one acquisition time period comprises the start time and the end time of acquisition, one end time corresponds to one moment, and each field of data stores the data according to the end time of the acquisition time period, so that the time for storing each field of data is the moment corresponding to the end time of the field of data.

In an alternative embodiment, the S11 includes:

s111, extracting signal energy and noise energy of all distance elements from one field of data every day to obtain a signal energy and noise energy list, wherein the signal energy and noise energy list comprises a plurality of frequency points, and each frequency point comprises actual signal power and actual noise power corresponding to each distance element;

s112, determining the mean value of the actual signal power of all the frequency points and the variance between the actual signal power of each frequency point and the mean value for each distance element based on the signal energy and noise energy list, and taking the actual signal power of the frequency point corresponding to the minimum variance value as the signal power of the distance element to obtain the signal power of all the distance elements;

determining the average value of the actual noise power of the frequency points on two sides in all the frequency points for each distance element based on the signal energy and noise energy list, and taking the average value as the noise power of the distance element to obtain the noise power of all the distance elements, wherein the number of the frequency points on two sides is 1/4 of the number of all the frequency points;

s113, obtaining a signal-to-noise ratio corresponding to each distance element based on the signal power of each distance element and the noise power of each distance element.

In an alternative embodiment, in S13, when the first snr threshold lookup table is time-padded,

and the signal-to-noise ratios corresponding to the distance elements at the lacking moment are obtained by performing interpolation calculation on the signal-to-noise ratios corresponding to the distance elements at the moments before and after the lacking moment.

In an alternative embodiment, the S15 includes:

s151, determining the mean value and the median value of the signal-to-noise ratio for all the signal-to-noise ratios in the current moment in the sequence table;

s152, in the sequence table, for each signal-to-noise ratio at the current moment, determining a first difference between the signal-to-noise ratio and the mean value of the signal-to-noise ratio and a second difference between the signal-to-noise ratio and the median value of the signal-to-noise ratio to obtain the sum of absolute values of the first difference and the second difference;

s153, regarding the current distance element at the current moment in the sequence table, taking the signal-to-noise ratio corresponding to the minimum value of the sum of absolute values as the signal-to-noise ratio threshold value corresponding to the current distance element at the current moment;

s154, repeating S151-S153 for each distance element at each moment in the sequence table to obtain the signal-to-noise ratio threshold corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold lookup table with the moment and the distance elements as indexes.

In an alternative embodiment, the S2 includes:

s21, actual working time by radarThe starting time of the SNR threshold lookup table with the time and the distance element as indexesAnd time interval of radar samplingObtaining a time index；

S22, obtaining a distance element index according to the difference between the actual distance element and the initial distance element;

and S23, extracting the SNR threshold corresponding to the time index and the distance element from the SNR threshold lookup table using the time and the distance element as indexes.

For example, the method of the present invention adopts the following process:

step 1, collecting radar sampling data (historical radar sampling data in a preset time period) of a week of a monitoring sea area, extracting signal energy and noise energy of all distance elements of each field of data every day, obtaining a list of the signal energy and the noise energy, and storing the list according to the day.

As shown in table 1, a list of signal energy and noise energy for Day one Day1 is shown, where StationName _ YYMMD1_ HHMMS1_ PtSum _ chsum.ft1, StationName _ YYMMD1_ HHMMS2_ PtSum _ chsum.ft1, … …, and StationName _ YYMMD1_ HHMMSs _ PtSum _ chsum.ft1 represent each frequency bin, respectively.

For the frequency points StationName _ YYMMD1_ HHMMS1_ PtSum _ chsum.ft1, S1list, N1 respectively represent the actual signal power and the actual noise power corresponding to the distance element 1, S2list, N2 respectively represent the actual signal power and the actual noise power corresponding to the distance element 2, S3list, N3 respectively represent the actual signal power and the actual noise power corresponding to the distance element 3, and … …, Snlist, Nn respectively represent the actual signal power and the actual noise power corresponding to the distance element N. The actual signal power and the actual noise power corresponding to each distance element of other frequency points in table 1 are described as frequency points StationName _ YYMMD1_ HHMMS1_ PtSum _ chsum.ft1, and are not described herein again.

TABLE 1

And 2, calculating the mean value of the actual signal power of all the frequency points and the variance of the actual signal power of each frequency point relative to the mean value for each distance element in each field of data, and taking the actual signal power of the frequency point corresponding to the minimum variance value as the signal power of the distance element. Correspondingly, for each distance element in each field of data, calculating the average value of the actual noise power of the frequency points on two sides in all the frequency points, and taking the average value as the noise power of the distance element, wherein the number of the frequency points on two sides is 1/4 of the number of all the frequency points.

And 3, calculating the signal-to-noise ratio corresponding to each distance element according to the signal power of each distance element obtained in the step 2 and the noise power of each distance element obtained in the step 1, and obtaining the signal-to-noise ratio corresponding to each distance element in the field data.

For the time of day, there are multiple fields of data, repeat step 1-3 for each field of data, can get the correspondent signal-to-noise ratio of every distance element of the multiple fields of data in the time of day, get the threshold lookup table of the first signal-to-noise ratio. As shown in table 2, a first signal-to-noise ratio threshold lookup table for one day is shown, and YYMMD1_ HHM1SS, YYMMD1_ HHM2SS, … …, and YYMMD1_ HHMMSS respectively represent signal-to-noise ratios corresponding to distance element 1, distance element 2, distance element 3, … …, and distance element N when time HHM1SS of the first day, time HHM1SS, … … of the first day, and time HHMMSS of the first day, and SNR11, SNR12, SNR13, … …, and SNR1N respectively represent time HHM1SS of the first day.

TABLE 2

And 4, according to the total field number of the radar data (namely the theoretical value of the total number of the radar single-field data files) every day, time completion is carried out on the first signal-to-noise ratio threshold lookup table, and the signal-to-noise ratio at the missing moment is obtained through interpolation of front and back time points to obtain a second signal-to-noise ratio threshold lookup table.

And 5, respectively extracting elements at the same position from a second signal-to-noise ratio threshold lookup table every day in a week to form a sequence table. As shown in table 3, the partial sequence listing shows that, at time HHM1SS, the signal-to-noise ratios Day 1T 1-R1, Day 2T 1-R1, Day3T1-R1, … …, and Day 7T 1-R1 respectively represent the signal-to-noise ratio of distance element 1 at time HHM1SS on the first Day, the signal-to-noise ratio of distance element 1 at time HHM1SS on the second Day, the signal-to-noise ratio of distance element 1 at time HHM1SS on the third Day, … …, and the signal-to-noise ratio of distance element 1 at time HHM1SS on the seventh Day.

TABLE 3

The mean and median of all the snrs for each time in the sequence table are calculated separately, for example, when the time HHM1SS is calculated, the mean and median of the snrs for the distance cell 1 at the time HHM1SS on the first day, the distance cell 1 at the time HHM1SS on the second day, the distance cell 1 at the time HHM1SS on the third day, the distance cell 1 at … …, and the distance cell 1 at the time HHM1SS on the seventh day.

And 6, respectively calculating the sum of the absolute values of the mean difference and the median difference obtained in the step 5 and each element in each moment in the sequence table, and taking the signal-to-noise ratio corresponding to the minimum value of the sum of the absolute values as the signal-to-noise ratio threshold of the moment and the distance element. For example, the signal-to-noise ratio of distance bin 1 at time HHM1SS on the third day in table 3 is taken as the signal-to-noise ratio threshold for time HHM1SS and distance bin 1.

And 7, repeating the steps 4-6 on the first signal-to-noise ratio threshold lookup table obtained in the step 3 for 7 days a week to obtain a signal-to-noise ratio threshold lookup table with the time and the distance element as indexes. As shown in table 4, at time t0, the SNR thresholds for range bin 1, range bin 2, range bins 3, … …, and range bin N are SNR01, SNR02, SNR03, … …, and SNR0N, respectively.

TABLE 4

Step 8, passing the time of the data file during actual useReference starting time in SNR threshold lookup table with time and distance element as indexAnd data file generation time intervalTo obtain the time indexThe time index serves as a time stamp. The distance element index is obtained by the difference between the actual distance element and the starting distance element of the grid. And obtaining the corresponding signal-to-noise ratio threshold value through the time index and the distance element index.

The method comprises the steps of dividing grid units in advance according to the scanning range of the radar, dividing a frame of radar echo image into a plurality of azimuth units in the azimuth dimension, dividing the range dimension of each azimuth unit into a plurality of distance units, and enabling one distance unit in each azimuth unit to form one grid unit.

The embodiment of the invention provides a system for determining a first-order peak signal-to-noise ratio threshold of a high-frequency ground wave radar, which comprises:

the signal-to-noise ratio threshold lookup table determining module is used for generating a signal-to-noise ratio threshold lookup table with time and distance elements as indexes according to radar echo signal energy and noise energy data of historical radar sampling data in a preset time period, wherein the signal-to-noise ratio threshold lookup table with the time and the distance elements as indexes comprises a plurality of times, and each time comprises a signal-to-noise ratio threshold corresponding to each distance element;

and the signal-to-noise ratio threshold extraction module is used for extracting the signal-to-noise ratio threshold corresponding to the actual working time and the actual distance element from the signal-to-noise ratio threshold lookup table which takes the moment and the distance element as indexes according to the actual working time and the actual distance element of the radar.

In an optional implementation, the snr threshold lookup table determining module includes:

processing the actual signal power and the actual noise power of each distance element for one field of data in each day to obtain the signal-to-noise ratio corresponding to each distance element;

obtaining a first signal-to-noise ratio threshold lookup table based on signal-to-noise ratios corresponding to distance elements of multiple fields of data every day, wherein the first signal-to-noise ratio threshold lookup table comprises multiple moments in a day, and each moment comprises the signal-to-noise ratio corresponding to each distance element;

according to the preset time number, time completion is carried out on the first signal-to-noise ratio threshold lookup table to obtain a second signal-to-noise ratio threshold lookup table;

extracting elements at the same position in each second signal-to-noise ratio threshold lookup table in a preset time period to form a sequence table, wherein the same position represents the signal-to-noise ratio corresponding to the same distance element at the same time, the sequence table comprises a plurality of times, and each time comprises the signal-to-noise ratio corresponding to the same distance element at each day;

and processing the signal-to-noise ratio corresponding to the same distance element on each day at each moment in the sequence list to obtain the signal-to-noise ratio threshold value corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold value lookup table with the moment and the distance elements as indexes.

In an optional embodiment, the processing the actual signal power and the actual noise power of each distance element for one field of data per day to obtain the signal-to-noise ratio corresponding to each distance element includes:

extracting signal energy and noise energy of all distance elements from one field of data every day to obtain a signal energy and noise energy list, wherein the signal energy and noise energy list comprises a plurality of frequency points, and each frequency point comprises actual signal power and actual noise power corresponding to each distance element;

determining the mean value of the actual signal power of all the frequency points and the variance between the actual signal power of each frequency point and the mean value for each distance element based on the signal energy and noise energy list, and taking the actual signal power of the frequency point corresponding to the minimum variance value as the signal power of the distance element to obtain the signal power of all the distance elements; determining the average value of the actual noise power of the frequency points on two sides in all the frequency points for each distance element based on the signal energy and noise energy list, and taking the average value as the noise power of the distance element to obtain the noise power of all the distance elements, wherein the number of the frequency points on two sides is 1/4 of the number of all the frequency points;

and obtaining the signal-to-noise ratio corresponding to each distance element based on the signal power of each distance element and the noise power of each distance element.

In an alternative embodiment, in time-filling the first snr threshold lookup table,

and the signal-to-noise ratios corresponding to the distance elements at the lacking moment are obtained by performing interpolation calculation on the signal-to-noise ratios corresponding to the distance elements at the moments before and after the lacking moment.

In an optional implementation manner, the processing, in the sequence table, the signal-to-noise ratio corresponding to the same distance element on each day at each time to obtain a signal-to-noise ratio threshold corresponding to each distance element at each time, and generating a signal-to-noise ratio threshold lookup table using the time and the distance element as an index includes:

in the sequence table, determining the mean value and the median value of the signal-to-noise ratios of all the signal-to-noise ratios at the current moment;

in the sequence table, for each signal-to-noise ratio at the current moment, determining a first difference between the signal-to-noise ratio and the mean value of the signal-to-noise ratio and a second difference between the signal-to-noise ratio and the median value of the signal-to-noise ratio to obtain the sum of absolute values of the first difference and the second difference;

in the sequence table, for the current distance element at the current moment, taking the signal-to-noise ratio corresponding to the minimum value of the sum of absolute values as the signal-to-noise ratio threshold value corresponding to the current distance element at the current moment;

and repeating the steps for each distance element at each moment in the sequence table to obtain the signal-to-noise ratio threshold corresponding to each distance element at each moment, and generating a signal-to-noise ratio threshold lookup table with the moment and the distance elements as indexes.

In an optional implementation, the snr threshold extraction module includes:

by actual operating time of the radarThe starting time of the SNR threshold lookup table with the time and the distance element as indexesAnd time interval of radar samplingObtaining a time index；

Obtaining a distance element index according to the difference between the actual distance element and the initial distance element;

and extracting the signal-to-noise ratio threshold value corresponding to the time index and the distance element from the signal-to-noise ratio threshold value lookup table taking the time and the distance element as indexes.

The disclosure also relates to an electronic device comprising a server, a terminal and the like. The electronic device includes: at least one processor; a memory communicatively coupled to the at least one processor; and a communication component communicatively coupled to the storage medium, the communication component receiving and transmitting data under control of the processor; wherein the memory stores instructions executable by the at least one processor to implement the method of the above embodiments.

In an alternative embodiment, the memory is used as a non-volatile computer-readable storage medium for storing non-volatile software programs, non-volatile computer-executable programs, and modules. The processor executes various functional applications of the device and data processing, i.e., implements the method, by executing nonvolatile software programs, instructions, and modules stored in the memory.

The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store a list of options, etc. Further, the memory may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and such remote memory may be connected to the external device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

One or more modules are stored in the memory and, when executed by the one or more processors, perform the methods of any of the method embodiments described above.

The product can execute the method provided by the embodiment of the application, has corresponding functional modules and beneficial effects of the execution method, and can refer to the method provided by the embodiment of the application without detailed technical details in the embodiment.

The present disclosure also relates to a computer-readable storage medium for storing a computer-readable program for causing a computer to perform some or all of the above-described method embodiments.

That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Furthermore, those of ordinary skill in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

It will be understood by those skilled in the art that while the present invention has been described with reference to exemplary embodiments, various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.