阅读说明：本技术 一种多基站雷达构型下的距离扩展目标检测方法 (Method for detecting distance extension target under multi-base-station radar configuration ) 是由 李军 何瑞华 李猛 尉泽华 鲍志宇 龚凯峰 于 2020-05-20 设计创作，主要内容包括：本发明公开了一种多基站雷达构型下的距离扩展目标检测方法,包括：建立多基站雷达系统中的局部雷达站的距离扩展目标模型；对局部雷达站的观测数据进行匹配滤波处理,构建全局观测量；为各局部雷达站设置权值,并得到全局观测量的一阶矩和二阶矩；由偏移系数最大化构建权值优化问题,计算系统整体偏移系数,求出偏移系数最大化时所对应的局部雷达站的最优权值矢量；对各局部雷达站进行信息融合得到全局检测统计量,并设置检测门限；根据检测门限判决目标是否存在。本发明将多基站雷达系统模型与距离扩展目标检测问题相结合,并利用偏移系数最大化求解最优权值,使得能够有效提升局部雷达检测信息融合后对距离扩展目标的检测性能。(The invention discloses a method for detecting a range extension target under a multi-base-station radar configuration, which comprises the following steps: establishing a distance extended target model of a local radar station in a multi-base station radar system; carrying out matched filtering processing on observation data of a local radar station to construct a global observation quantity; setting weights for each local radar station, and obtaining a first moment and a second moment of the global observed quantity; constructing a weight optimization problem by maximizing the offset coefficient, calculating the overall offset coefficient of the system, and solving the optimal weight vector of the corresponding local radar station when the offset coefficient is maximized; carrying out information fusion on each local radar station to obtain global detection statistics, and setting a detection threshold; and judging whether the target exists or not according to the detection threshold. According to the method, a multi-base-station radar system model and the distance extension target detection problem are combined, and the optimal weight is solved by utilizing the offset coefficient in a maximized mode, so that the detection performance of the distance extension target after local radar detection information is fused can be effectively improved.)

1. A method for detecting a range extension target under a multi-base station radar configuration is characterized by comprising the following steps:

step 1: establishing a distance extended target model of a local radar station in a multi-base station radar system;

step 2: performing matched filtering processing on the observation data of the local radar station, and constructing a global observation quantity after modular squaring;

and step 3: setting a weight for each local radar station by calculating the statistical characteristic of the local observed quantity of each local radar station, and obtaining a first moment and a second moment of the global observed quantity;

and 4, step 4: building a weight optimization problem according to the maximization of the offset coefficient, calculating the overall offset coefficient of the system according to the statistical characteristics of the global observed quantity in the step 3, and solving the optimal weight vector of the corresponding local radar station when the offset coefficient is maximized;

and 5: carrying out information fusion on each local radar station to obtain global detection statistics, and setting a detection threshold according to the false alarm probability of a given system;

step 6: and judging whether the target exists or not according to the detection threshold.

2. The method for detecting the extended-range target under the multi-base-station radar configuration according to claim 1, wherein the step 1 specifically comprises:

establishing a range extension target model of a local radar station of a multi-base-station radar system, wherein the multi-base-station radar system comprises a self-transmitting and self-receiving radar station and M-1 receiving stations, and the echo signal of a receiving channel corresponding to the mth receiving station is

Wherein K represents the number of scattering points,representing the noise term of each receive channel and obeying a zero mean gaussian distribution, β_mkRepresenting channel propagationGain, s denotes the transmitted signal, propagation attenuation_mIs defined as:

wherein d is₁Representing the distance of the center of the object from the transmitting station, d_mRepresenting the distance of the target centre from the receiving station, the time delay tau_m＝(d₁+d_m) And c are the speed of light.

3. The method for detecting extended range targets in a multi-base-station radar configuration according to claim 2, wherein the step 2 specifically comprises:

(2a) performing matched filtering processing on observation data of the local radar station, constructing a global observation quantity after modular squaring, matching M paths of target echo signals at a receiving end by using a matched filter, and for each path of target echo signal, using H to perform matching₁Indicating the presence of a target detected by the system in the detection unit, H₀The system detects that the target does not exist in the detection unit, and the target detection problem is summarized as follows:

wherein r is_mRepresenting received data of the m-th receiving station, propagation attenuation for a given target position_mIs constant and assumes the noise term n of the mth channel_mObedience mean is zero and variance isComplex gaussian distribution of (a);

(2b) constructing global observation of the multi-base-station radar system, wherein M independent observations of the whole multi-base-station radar system are as follows:

R＝[r₁,r₂,...,r_M]^T

let z_m＝|r_m|²Representing each received dataAnd (3) modulo square, then the global observation collected by the fusion center is represented as:

Z＝[z₁,z₂,...,z_M]^T

4. the method for detecting extended range targets in a multi-base-station radar configuration according to claim 3, wherein the step 3 specifically comprises:

(3a) calculating statistical characteristics of local observed quantities of each local radar station, at H₀Under the assumption, the probability density function of the local radar station is:

at H₁Under the assumption that the probability density function of the local radar station is

Wherein the content of the first and second substances,

in a similar manner, in H₀Under the assumption, the first moment is defined as mu_0mDefining second order momentsIs var_0mAnd then:

(3b) calculating the statistical characteristic of the global observed quantity, and setting the weight vector of the multi-base station radar system as w ═ w₁,w₂,...,w_M]^TThen the global detection statistic is represented asDetection statistic Z_cFirst moment ofAnd a second moment var [ Z ]_c]Expressed as:

wherein the content of the first and second substances,

u₀＝[μ₀₁,μ₀₂,...,μ_0M]^T

u₁＝[μ₁₁,μ₁₂,...,μ_1M]^T

Σ₀＝diag([var₀₁,var₀₂,...,var_0M]^T)

Σ₁＝diag([var₁₁,var₁₂,...,var_1M]^T)。

5. the method for detecting extended-range targets in a multi-base-station radar configuration according to claim 4, wherein the step 4 specifically comprises:

solving the optimal weight vector by utilizing the maximum of the offset coefficient, solving the weight of each local radar station according to the first moment and the second moment deduced in the step 3, and firstly substituting the solved weight into the offset coefficient to obtain

Order to

w₁＝(Σ₁+Σ₀)¹²w

c＝(Σ₁+Σ₀)^-12(u₁-u₀)

The offset coefficient is then expressed as:

using rayleigh entropy:

the maximum eigenvalue of matrix B is known to satisfy:

2Bw₁＝λ_maxw₁

since the rank of matrix B is 1, then:

λ_max＝||c||²

and has a_max≥d²(w) when w₁Lambda is the eigenvector corresponding to the B maximum eigenvalue_max≥d²The equal sign in (w) holds true,

after normalization, the optimal weight is finally expressed as:

wherein each element corresponds to a weight coefficient, w, of a different local radar station_opt＝[w₁,w₂,…,w_M]^T。

6. The method for detecting extended-range targets in a multi-base-station radar configuration according to claim 5, wherein the step 5 specifically comprises:

setting a detection threshold according to the false alarm probability of a given system, wherein the false alarm probability is expressed as:

wherein

wherein

Technical Field

The invention belongs to the technical field of radars, and particularly relates to a method for detecting a distance extension target under a multi-base-station radar configuration, which is suitable for improving the detection performance of the distance extension target under a multi-base-station radar system.

Background

The traditional phased array radar is very sensitive to fluctuation of target fusion communication (RCS) due to a single irradiation angle, and is greatly influenced by factors such as target attitude, target shape and the like. The transmitting stations and the receiving stations of the multi-base-station radar are separately arranged, the distance between the stations is far, and compared with the traditional phased array radar, the space diversity gain of a target can be obtained. However, the multi-base station radar system has new problems in actual target detection.

Firstly, when each radar station of the multi-base-station radar system is sparsely distributed, the difference between the radar transmitting-receiving distance and the target detection distance is smaller, the detection environments of the stations are different, the channel attenuation of the receiving channels of the radar stations is different, and the detection performance of local stations is different. In addition, when the size of the target is large and the target is a distance extension target, the target is composed of a plurality of scattering points and is distributed in a plurality of distance resolution units, and according to a double-base radar equation, a signal-to-noise ratio contour line of the distance resolution unit where each scattering point is located is not overlapped with a distance contour line any more, so that the detection performance of the radar system on each scattering point is different. When the fusion center of the multi-base-station radar system fuses the observed quantities of each local station, if the weights allocated to the observed quantities of each local station are consistent, the detection performance is reduced.

Disclosure of Invention

Aiming at the problem of distance extended target detection, the invention combines the configuration of a multi-base station radar system, observes a plurality of scattering points of a distance extended target by utilizing a plurality of receiving channels in space, and obtains the optimal weight of a local station by taking the maximization of an offset coefficient as constraint, thereby realizing the effective fusion of multi-channel data and further improving the detection performance of the radar system. In order to achieve the above object, the embodiments of the present invention are implemented by the following technical solutions.

A method for detecting a range extension target under a multi-base station radar configuration comprises the following steps:

step 1: establishing a distance extended target model of a local radar station in a multi-base station radar system;

step 2: performing matched filtering processing on the observation data of the local radar station, and constructing a global observation quantity after modular squaring;

and step 3: setting a weight for each local radar station by calculating the statistical characteristic of the local observed quantity of each local radar station, and obtaining a first moment and a second moment of the global observed quantity;

and 4, step 4: building a weight optimization problem according to the maximization of the offset coefficient, calculating the overall offset coefficient of the system according to the statistical characteristics of the global observed quantity in the step 3, and solving the optimal weight vector of the corresponding local radar station when the offset coefficient is maximized;

and 5: carrying out information fusion on each local radar station to obtain global detection statistics, and setting a detection threshold according to the false alarm probability of a given system;

step 6: and judging whether the target exists or not according to the detection threshold.

The invention has the following advantages: (1) the method for detecting the distance extension target under the multi-base-station radar configuration obtains space diversity gain by using the multi-base-station radar system configuration, and when the number of radar base stations is increased, the detection performance is also increased; (2) the offset coefficient maximization is used as a constraint distribution weight, the output signal-to-noise ratio level of the whole radar system is higher, and compared with the weight of each local radar station, the detection performance is improved; (3) the different forms of the offset coefficients have different effects on the detection performance, and the selected form of the offset coefficients contains the target information, which improves the performance compared with the original offset coefficients containing only noise information.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.

Fig. 1 is a schematic flowchart of a method for detecting a range expansion target in a multi-base-station radar configuration according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a multi-base-station radar target detection scene;

fig. 3 is a graph showing a false alarm probability of a method for detecting a range extension target in a multi-base-station radar configuration, which is provided by an embodiment of the present invention, varying with a detection threshold;

fig. 4 is a comparison diagram of detection probability of a distance extended target detection method under a multi-base station radar configuration according to an embodiment of the present invention and a detection probability of a conventional method varying with false alarm probability;

fig. 5 is a comparison diagram of detection probability of a distance extension target detection method and an NDC weight solving method according to the embodiment of the present invention, which is varied with false alarm probability;

fig. 6 is a comparison graph of change curves of detection probability with channel signal-to-noise ratio when the number of radar base stations is changed by the method for detecting a range extension target in a multi-base-station radar configuration according to the 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 some embodiments, not all embodiments, of the present invention. 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.

Referring to fig. 1, the present invention provides the following technical solutions: a method for detecting a range extension target under a multi-base-station radar configuration specifically comprises the following steps:

step 1, establishing a range extension target model of a local radar station of a multi-base-station radar system, where the multi-base-station radar system includes a self-transmitting and self-receiving radar station and M-1 receiving stations, that is, includes 1 transmitting end and M receiving ends, a target detection scene is shown in fig. 2, and an echo signal of a receiving channel corresponding to an mth receiving station is:

wherein K represents the number of scattering points, K represents the K-th scattering point,subject to a zero mean Gaussian distribution for the noise term of each receive channel, β_mkRepresenting the channel propagation gain, β_mkIs formed by merging scattering coefficient, radar transmitting power, antenna gain and other constant parameters, and can be regarded as that the obedience mean value is 0, and the variance isComplex gaussian distribution of (1), s denotes the transmitted signal, propagation attenuation_mIs defined as:

wherein d is₁Distance of target center to transmitting station, d_mTime delay tau for the distance from the target centre to the receiving station_m＝(d₁+d_m) And c are the speed of light.

And 2, performing matched filtering processing on observation data of the local radar stations, constructing a global observation quantity after modular squaring, and matching M paths of target echo signals at a receiving end by using a matched filter. For each target echo signalIn other words, the target detection problem is reduced to the following binary hypothesis testing problem, using H₁Indicating the presence of a target detected by the system in the detection unit, H₀Indicating that the system detected the absence of the target in the detection unit. The target detection problem is summarized as:

wherein r is_mRepresenting the received data of the m-th receiving station, as known from the definition of the propagation attenuation, for a given target position_mThe noise term after matched filtering is different from that in the previous receiving channel for a constant, and now assume that the noise term n of the mth receiving channel_mObedience mean is zero and variance is

Complex gaussian distribution. The M independent observations of the whole distributed multi-base-station radar system are as follows:

R＝[r₁,r₂,...,r_M]^T

let z_m＝|r_m|²And represents the square of the modulus of each received data, the observed quantity collected by the fusion center is represented in the form of a vector:

Z＝[z₁,z₂,...,z_M]^T

step 3, calculating the statistical characteristics of the local observed quantities of all the local radar stations to obtain a first moment and a second moment of the global observed quantities, wherein the first moment and the second moment are in H₀Under the assumption, due to z_mThe probability density function of (a) follows an exponential distribution, so the PDF (probability density function) of the local radar station is expressed as:

at H₁Under the assumption that

Wherein the content of the first and second substances,for the noise term n_mThe variance of (a) is determined,propagate gain β for the channel_mkThe variance of (c).

According to the form of the mean and variance of the exponential distribution, at H₁Under the assumption, an observed quantity z is defined_mFirst moment of_1mDefining the second moment as var_1mThen there is

In a similar manner, in H₀Under the assumption, the first moment is defined as mu_0mDefining the second moment as var_0mIs provided with

Setting the weight vector of the multi-base station radar system as w ═ w₁,w₂,...,w_M]^TThen the global detection statistic can be expressed asGlobal detection statistic Z_cFirst moment ofAnd a second moment var [ Z ]_c]Can be expressed as follows:

wherein the content of the first and second substances,

u₀＝[μ₀₁,μ₀₂,...,μ_0M]^T

u₁＝[μ₁₁,μ₁₂,...,μ_1M]^T

Σ₀＝diag([var₀₁,var₀₂,...,var_0M]^T)

Σ₁＝diag([var₁₁,var₁₂,...,var_1M]^T)

and 4, step 4: solving the optimal weight vector by utilizing the maximization of the offset coefficient, solving the weight of each local radar station according to the first moment and the second moment deduced in the step 3, and firstly substituting the solved weight into the offset coefficient to obtain

Unfold the above formula

w₁＝(Σ₁+Σ₀)¹²w

c＝(Σ₁+Σ₀)^-12(u₁-u₀)

The offset coefficient can be expressed as:

using rayleigh entropy:

the maximum eigenvalue of matrix B is known to satisfy:

2Bw₁＝λ_maxw₁

since the rank of matrix B is 1, then:

λ_max＝||c||²

and has a_max≥d²(w) when w₁Lambda is the eigenvector corresponding to the B maximum eigenvalue_max≥d²The equal sign in (w) holds. After normalization, the optimal weight is finally expressed as:

as can be seen from the above formula, w_optColumn vector of dimension M × 1, where each element corresponds to weight coefficient of different local radar stations, i.e. w_opt＝[w₁,w₂,…,w_M]^T。

And 5: and carrying out information fusion on each local radar station to obtain global detection statistics, and setting a detection threshold according to the false alarm probability of a given system. The false alarm probability can be expressed as the following expression:

wherein

The detection probability can be expressed as

Wherein

Specifically, it is assumed that the variable weighted by the random quantity subjected to the standard exponential distribution is Λ.

At H₁Under the assumption, the m-th local mineConverting the observed quantity of the receiving channel of the arrival station into standard exponential distribution, equivalently converting the weight coefficient of the arrival station into the standard exponential distribution

At this time defineIs H₁The following weight vector is assumed. At this time, the detection probability may be expressed as

Pd＝1-F_Λ(η|H₁)

Where η is the detection threshold, F_Λ(η|H₁) Is H₁Assuming a cumulative distribution function of Λ, the probability density function of Λ can be expressed as

Integrating the above equation to obtain

When the detection threshold is eta, the detection probability is

In a similar manner, in H₀Under the assumption, the observed quantity of the receiving channel of the mth local radar station is converted into standard exponential distribution, equivalently, the weight coefficient of the station is converted into standard exponential distribution

At this time defineIs H₀The following weight vector is assumed. The false alarm probability is then expressed as

And 6, judging whether the target exists according to the detection threshold in the step 5.

The method for detecting the distance extension target under the multi-base-station radar configuration, provided by the embodiment of the invention, comprises the steps of establishing a distance extension target echo model, obtaining local observed quantity through matched filtering, then constructing global observed quantity, solving the first-order and second-order statistical characteristics of the global observed quantity, obtaining the optimal weight vector under the maximum constraint of an offset coefficient, finally obtaining the detection statistic after the signals of all local radar stations are fused, and realizing the detection of the distance extension target under the multi-base-station radar configuration.

Simulation experiment: four sets of experiments were performed in the examples of the invention: experiment 1, a Monte Carlo simulation experiment is used for verifying the false alarm probability of the method provided by the embodiment of the invention, and the effectiveness and the correctness of the method provided by the embodiment of the invention are verified; experiment 2, comparing the method provided by the embodiment of the invention with the traditional method that the weights of all local radar stations are consistent, and verifying the detection performance of the method provided by the embodiment of the invention; experiment 3, the detection performance of the method of the embodiment of the present invention is further verified by comparing the method of the embodiment of the present invention with a most-weighted solution method in the form of NDC (normal deflection Coefficient); experiment 4, the method provided by the embodiment of the present invention is used to verify the target detection performance of the method provided by the embodiment of the present invention when the number of local radar stations is changed.

Experiment 1: the false alarm probability of the method provided by the embodiment of the invention is verified by using a Monte Carlo simulation experiment, and the effectiveness and the correctness of the method provided by the embodiment of the invention are verified. Setting simulation parameters: the number M of local radar stations is 4, the coordinates of each station are T/R (-80km,0), R₁(0,-80km)，R₂(80km,0),R₃(0,80km), noise power of each channel isThe reference signal-to-noise ratio of each channel is { snr }₀＝-3dB,snr₁＝3dB,snr₂＝5dB,snr₃10dB, the Monte Carlo test frequency is set to 10⁶The algorithm was verified by Monte Carlo test.

Referring to fig. 3, fig. 3 is a graph illustrating a false alarm probability of a distance extension target detection method under a multi-base station radar configuration according to an embodiment of the present invention varying with a detection threshold. As shown in fig. 3, when the decision threshold is continuously increased, the false alarm probability is gradually decreased, and it can be found by comparing the two curves that the theoretical false alarm probability value and the Monte Carlo test value of the method according to the embodiment of the present invention can be matched together in a substantially matching manner, thereby verifying the correctness of the proposed method and the validity of the obtained false alarm probability display expression.

Experiment 2: compared with the traditional method that the weight of each local radar station is consistent, the method provided by the embodiment of the invention is used for verifying the detection performance of the method provided by the embodiment of the invention. Setting simulation parameters: the number M of local radar stations is 4, and the noise power of each station is

The reference signal-to-noise ratio of each station receiving channel is { snr }₀＝-3dB,snr₁＝3dB,snr₂＝5dB,snr₃10dB, each station coordinate is T/R (-80km,0), R₁(0,-80km)，R₂(80km,0),R₃(0,80km), the performance of the method proposed by the embodiment of the present invention ("proposed method" in fig. 4) is analyzed and compared with the conventional method, where the conventional method considers the weights of the respective receiving channels to be consistent, i.e., the global statistics is a direct addition method of the local quantities.

Referring to fig. 4, fig. 4 is a comparison chart of detection probability of a distance extended target detection method under a multi-base station radar configuration according to an embodiment of the present invention and a conventional method as a function of false alarm probability. As shown in fig. 4, comparing the conventional method under the condition that the weights of the channels are the same with the method of constraining the weight coefficients by the offset coefficients in the embodiment of the present invention, it can be found that, when the reference signal-to-noise ratios of the channels are different, the method provided in the embodiment of the present invention has better performance than the conventional method, and under the constraint of the same false alarm probability, the detection probability of the method provided in the embodiment of the present invention is improved compared with the conventional method. The method provided by the embodiment of the invention considers the quality of detection performance of each station and the difference of signal-to-noise ratios of scattering points on a distance extension target in a weighted mode by restricting the observed quantity of each local radar station through a weight value under the conditions of a given target center distance and a reference signal-to-noise ratio, so that the relative distance of the global statistic PDF center under two assumptions is larger, and the output signal-to-noise ratio of the whole system is larger.

Experiment 3: the detection performance of the method provided by the embodiment of the invention is further verified by comparing the method provided by the embodiment of the invention with the most weighted solution method in the form of NDC (normalized difference coefficient) offset coefficient. The simulation parameters are set as follows: the number M of local radar stations is 4, the noise power of each channel is 1dB, and the reference signal-to-noise ratio of a receiving channel of each station is { snr }₀＝-3dB,snr₁＝3dB,snr₂＝5dB,snr₃10dB, each station coordinate is T/R (-80km,0), R₁(0,-80km)，R₂(80km,0),R₃(0,80km)。

Referring to fig. 5, fig. 5 is a comparison diagram of detection probabilities of a distance extension target detection method and an NDC weight solving method according to an embodiment of the present invention, the detection probabilities being changed with false alarm probabilities. As shown in fig. 5, the NDC method is close to the method of the embodiment of the present invention in detection performance, and the method of the embodiment of the present invention improves the detection performance of the system to some extent, but the effect is not very obvious. For analysis reasons, the denominator term of the offset coefficient in the NDC method only contains H₀Variance of observed quantity under assumption, neglecting H₁The assumed target information has a certain loss, and the denominator terms of the offset coefficients in the method provided by the embodiment of the invention all contain H₁The variance of the observed quantity is assumed.

Experiment 4: by using the method provided by the embodiment of the invention, the target detection performance of the method provided by the embodiment of the invention is verified when the number of the local radar stations is changed. And comparing the detection performance under three conditions of setting the number M of local radar stations to be 3, setting the number M to be 4 and setting the number M to be 5. The noise power of each station is set to be 1dB, the reference signal-to-noise ratio of each channel is consistent, and the distance between each station and the target center is set to be 80 km.

Referring to fig. 6, fig. 6 is a comparison graph of a curve of detection probability along with a change of a channel signal-to-noise ratio when the number of radar base stations is changed by the method for detecting a range extension target in a multi-base-station radar configuration according to an embodiment of the present invention. As shown in fig. 6, when the reference signal-to-noise ratio is larger, the detection probability is larger, and meanwhile, it can be known from comparison of the detection probabilities under different numbers of stations that the detection performance is better when the number of local radar stations is larger, which verifies that the detection performance is improved when the number of local radar stations is increased by the method provided by the embodiment of the present invention.

In conclusion, the simulation experiment verifies the correctness and the effectiveness of the method.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention; thus, if such changes and modifications of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is intended to include such changes and modifications. The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.