阅读说明：本技术 一种基于距离微分的虚假航迹剔除方法 (False track elimination method based on distance differentiation ) 是由 刘联节 于 2020-06-10 设计创作，主要内容包括：本发明公开了一种基于距离微分的虚假航迹剔除方法,解决复杂环境下的航迹的高虚警概率和高误告警律的问题,该方法是在原有经典处理算法的基础上增加了航迹距离微分多普勒速度和一次点迹多普勒速度一致性统计判别处理,不仅大幅降低了虚警概率,而且保证了对真实目标的有效跟踪。与现有技术相比,具有以下优点：采用统计方法而不是实时判断,避免了偶尔一次多普勒速度跳变造成航迹跟踪失败的问题；该方法采用计算航迹多普勒和点迹多普勒滤波器通道号差值,避免了航迹多普勒速度和点迹多普勒速度存在模糊,提高了相关正确性；较之传统的处理方法,该方法可大幅降低航迹虚警概率,经测试,虚假航迹数可降低1个数量级,效果明显。(The invention discloses a false track elimination method based on distance differentiation, which solves the problems of high false alarm probability and high false alarm law of a track in a complex environment. Compared with the prior art, the method has the following advantages: a statistical method is adopted instead of real-time judgment, so that the problem of track tracking failure caused by occasional Doppler velocity jump is avoided; the method adopts the calculation of the difference value between the track Doppler and the channel number of the track Doppler filter, thereby avoiding the ambiguity of the track Doppler speed and improving the correlation correctness; compared with the traditional processing method, the method can greatly reduce the false alarm probability of the flight path, and the false flight path number can be reduced by 1 order of magnitude through tests, so that the effect is obvious.)

1. A false track elimination method based on distance differentiation is characterized by comprising the following steps:

1) estimating the track predicted position at the arrival time of the point track:

predicting the flight path to the corresponding time of the associated point path according to the flight path filtering value at the previous time and the associated primary point path:

wherein, the delta t is the time difference value between the arrival moment of the point track and the last track filtering moment;

[x_py_pz_p]^Tthe predicted value of the flight path is taken as the predicted value;

[x_sy_sz_s]^Tfiltering the value for the flight path;

[x_vy_vz_v]^Tthe track filtering speed;

[x_ay_az_a]^Tfiltering acceleration for the track;

2) acquiring track distance differential at the arrival time of the point track:

the track radial speed R of the track at the moment is obtained by distance differentiation by utilizing the track predicted value_v；

3) Obtaining track Doppler and track Doppler filter channel number difference delta N_f：

Because the track Doppler velocity and the track Doppler velocity are fuzzy, the channel number of the filter is compared at this time, so that the velocity ambiguity can be avoided, and the method specifically comprises the following steps:

a) calculating track Doppler velocity F_d

Wherein C is the speed of light, and f is the radar frequency;

b) calculating the Doppler channel number N corresponding to the flight path_Track

N_Track＝mod(F_dPRI.n, n) formula-4;

wherein PRI is the pulse repetition period, n is the number of accumulated points, F_dIs the track doppler velocity;

c) calculating the difference between the track Doppler and the track Doppler filter channel number_f

ΔN_f＝N_Track-N_DotFormula-5;

wherein N is_DotFor the trace point corresponding to the Doppler channel number, N_TrackCalculating the Doppler channel number of the flight path;

4) updating Δ N_fMean and variance of sequences:

Δ N at the N +1 th time_fThe sample is denoted x_nThe mean value obtained at the nth time is AVE_nVariance is VAR_nThen, the formula is updated for the mean value at the time n + 1:

variance update formula:

5) judging whether the flight path is true or false:

when Δ N_fWhen the number of the sample points is more than n, starting track authenticity judgment, and if AVE (average amplitude variation) is detected, judging whether the true track is true or false, wherein the mean value and the variance of Doppler comparison of the true track are smaller_n<minAVE_nAnd VAR_n<minVAR_nWhen the flight path is considered as a real flight path, finishing outputting and reporting; if the condition is not satisfied, returning to the first step to wait for the subsequent sample points to perform processing judgment.

2. The false track elimination method based on distance differentiation according to claim 1, wherein the last time track filtering value in step 1) includes position filtering, velocity filtering and filtering update time information.

3. The false track elimination method based on distance differentiation according to claim 1, wherein 5 out of the n in step 5).

Technical Field

The invention relates to the technical field of radar information processing, in particular to a false track elimination method based on distance differentiation.

Background

For a general traditional radar, a target is tracked by using distance, azimuth and pitching (or height) information of an echo in a track processing process, when an external environment is complex, a large number of false tracks are generated due to the existence of a large number of false point tracks, and the problems of track tracking and the like are easily caused due to track association errors.

However, the traditional trace-point filtering technology is difficult to realize the fine processing of the radar on the trace-point trace in the complex and variable space environment.

The main method is to perform pulse pressure, Moving Target Detection (MTD) filtering and constant false alarm rate detection on radar echo signals, then perform point trace condensation and four-stage point trace filtering on detected suspicious point traces, and finally send the point traces meeting the conditions to a terminal. The method has the advantages that different types of false traces are removed in a targeted manner in a grading mode in the trace filtering part to obtain a certain trace filtering effect, but the quality of the remaining traces is still to be further improved from the final processing result, and meanwhile the multi-stage filtering strategy increases the possibility that the real target trace is judged as the false trace, so that the false alarm probability is improved.

Therefore, more information (trace point doppler velocity) needs to be mined and comprehensively applied in the trace processing, so that false trace points are eliminated greatly, and the trace false alarm probability and false alarm in a complex environment can be effectively reduced.

Disclosure of Invention

Aiming at the problems in the technical background, the invention aims to provide a false track removing method, which solves the problems of high false alarm probability and high false alarm rate of a track in a complex environment.

In order to achieve the above purpose, the invention adopts the technical scheme that:

a false track elimination method based on distance differentiation specifically comprises the following steps:

1) estimating the track predicted position at the arrival time of the point track:

predicting the flight path to the corresponding time of the associated point path according to the flight path filtering value at the previous time and the associated primary point path:

wherein, the delta t is the time difference value between the arrival moment of the point track and the last track filtering moment;

[x_py_pz_p]^Tthe predicted value of the flight path is taken as the predicted value;

[x_sy_sz_s]^Tfiltering the value for the flight path;

[x_vy_vz_v]^Tthe track filtering speed;

[x_ay_az_a]^Tacceleration is filtered for the track.

2) Acquiring track distance differential at the arrival time of the point track:

the track radial speed R of the track at the moment is obtained by distance differentiation by utilizing the track predicted value_v；

3) Obtaining track Doppler and track Doppler filter channel number difference delta N_f：

Because the track Doppler velocity and the track Doppler velocity are fuzzy, the channel number of the filter is compared at this time, so that the velocity ambiguity can be avoided, and the method specifically comprises the following steps:

a) calculating track Doppler velocity F_d

Wherein C is the speed of light, and f is the radar frequency;

b) calculating the Doppler channel number N corresponding to the flight path_Track

N_Track＝mod(F_dPRI.n, n) formula-4;

wherein PRI is the pulse repetition period, n is the number of accumulated points, F_dIs the track doppler velocity;

c) calculating the difference between the track Doppler and the track Doppler filter channel number_f

ΔN_f＝N_Track-N_DotFormula-5;

wherein N is_DotFor the trace point corresponding to the Doppler channel number, N_TrackIs the computed track doppler channel number.

4) Updating Δ N_fMean and variance of sequences:

Δ N at the N +1 th time_fThe sample is denoted x_nThe mean value obtained at the nth time is AVE_nVariance is VAR_nThen, the formula is updated for the mean value at the time n + 1:

variance update formula:

5) judging whether the flight path is true or false:

when Δ N_fWhen the number of the sample points is more than n, starting track authenticity judgment, and if AVE (average amplitude variation) is detected, judging whether the true track is true or false, wherein the mean value and the variance of Doppler comparison of the true track are smaller_n<minAVE_nAnd VAR_n<minVAR_nWhen the flight path is considered as a real flight path, finishing outputting and reporting; if the condition is not satisfied, returning to the first step to wait for the subsequent sample points to perform processing judgment.

Preferably, the last-time track filtering value in step 1) includes position filtering, speed filtering and filtering update time information.

Preferably, 5 of the n in step 5) are selected.

Compared with the prior art, the invention has the following advantages:

1) a statistical method is adopted instead of real-time judgment, so that the problem of track tracking failure caused by occasional Doppler velocity jump is avoided;

2) the method adopts the calculation of the difference value between the track Doppler and the channel number of the track Doppler filter, thereby avoiding the ambiguity of the track Doppler speed and improving the correlation correctness;

3) compared with the traditional processing method, the method can greatly reduce the false alarm probability of the flight path, and the false flight path number can be reduced by 1 order of magnitude through tests, so that the effect is obvious.

Detailed Description

The following detailed description will be given with reference to specific embodiments of the present invention. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.

A false track elimination method based on distance differentiation specifically comprises the following steps:

1) estimating the track predicted position at the arrival time of the point track:

predicting the flight path to the corresponding time of the associated point path according to the last time flight path filtering value (position filtering, speed filtering and filtering updating time) and the associated one-time point path:

wherein, the delta t is the time difference value between the arrival moment of the point track and the last track filtering moment;

[x_py_pz_p]^Tthe predicted value of the flight path is taken as the predicted value;

[x_sy_sz_s]^Tfiltering the value for the flight path;

[x_vy_vz_v]^Tthe track filtering speed;

[x_ay_az_a]^Tacceleration is filtered for the track.

2) Acquiring track distance differential at the arrival time of the point track:

the track radial speed R of the track at the moment is obtained by distance differentiation by utilizing the track predicted value_v；

3) Obtaining track Doppler and track Doppler filter channel number difference delta N_f：

Because the track Doppler velocity and the track Doppler velocity are fuzzy, the channel number of the filter is compared at this time, so that the velocity ambiguity can be avoided, and the method specifically comprises the following steps:

d) calculating track Doppler velocity F_d

Wherein C is the speed of light, and f is the radar frequency;

e) calculating the Doppler channel number N corresponding to the flight path_Track

N_Track＝mod(F_dPRI.n, n) formula-4;

wherein PRI is the pulse repetition period, n is the number of accumulated points, F_dIs the track doppler velocity;

f) calculating the difference between the track Doppler and the track Doppler filter channel number_f

ΔN_f＝N_Track-N_DotFormula-5;

wherein N is_DotFor the trace point corresponding to the Doppler channel number, N_TrackIs the computed track doppler channel number.

4) Updating Δ N_fMean and variance of sequences:

Δ N at the N +1 th time_fThe sample is denoted x_nThe mean value obtained at the nth time is AVE_nVariance is VAR_nThen, the formula is updated for the mean value at the time n + 1:

variance update formula:

5) judging whether the flight path is true or false:

when Δ N_fWhen the number of the sample points is more than n (5), starting track authenticity judgment, and if AVE (average value and variance of Doppler comparison of real tracks are small_n<minAVE_nAnd VAR_n<minVAR_nWhen the flight path is considered as a real flight path, finishing outputting and reporting; if the condition is not satisfied, returning to the first step to wait for the subsequent sample points to perform processing judgment.

Compared with the prior art, the method adopts a statistical method instead of real-time judgment, and avoids the problem of track tracking failure caused by occasional Doppler velocity jump; the method adopts the calculation of the difference value between the track Doppler and the channel number of the track Doppler filter, thereby avoiding the ambiguity of the track Doppler speed and improving the correlation correctness; compared with the traditional processing method, the method can greatly reduce the false alarm probability of the flight path, and the false flight path number can be reduced by 1 order of magnitude through tests, so that the effect is obvious.

The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are merely illustrative of the principles of the invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.