Determination and application of STAP evaluation model for multi-channel array radar under non-ideal clutter

Abstract

The invention discloses a method for determining and applying a STAP evaluation model under non-ideal clutter of a multi-channel array radar, including: determining a multi-channel space-time two-dimensional receiving signal model according to radar system parameters; determining a discrete clutter data vector model of only the spatial dimension of the current unit to be detected under post-Doppler processing based on the multi-channel space-time two-dimensional receiving signal model, which includes a disturbance component introduced by a non-ideal orthogonal waveform; determining a multi-channel data vector model of non-ideal factors of the current unit to be detected; determining a clutter covariance matrix including non-ideal factors; determining an expression of a STAP clutter suppression weight vector according to; determining a STAP evaluation model under non-ideal factors according to the expressions of, and an output SCNR loss model. The invention can determine a more practical and accurate output SCNR loss model to guide the optimization of system parameters and STAP algorithm, thereby significantly improving the target detection capability of the system.

Description

Technical Field

[0001] The invention belongs to the technical field of radars, and in particular relates to a STAP evaluation model determination and application method for a multi-channel array radar under non-ideal clutter. Background Art

[0002] Airborne / space-based radars face severe clutter interference in the process of detecting targets. The uneven geographical features of the detection background, the fluctuation of elevation, and the dynamic activities of the ground objects make the clutter distribution have time-space dependence (non-uniform and non-stationary), as well as the non-ideal orthogonal waveform of the system and the non-ideal arrangement of the sensor array. These factors will cause the radar detection performance to be significantly reduced. It is easy to cause the risk that the radar system cannot achieve the expected design indicators in practical applications. Therefore, reasonable modeling and accurate estimation of the impact of the above non-ideal factors in the system design stage will help optimize the system parameters and algorithms, thereby improving the target detection capability of the system. According to existing research, when the covariance matrix of the clutter is accurately known, a simple method can be used to accurately approximate the performance of Space Time Adaptive Processing (STAP) in a statistical sense. Therefore, a large number of studies have focused on establishing a multi-waveform STAP framework, an empirical model of the performance of ground moving target indication (GMTI) for multi-input multi-output (MIMO) radars, and an analytical expression of the signal-to-clutter-plus-noise ratio (SCNR) loss of STAP processing for positive side-looking array radars. However, these theoretical models are based on the assumptions of ideal clutter distribution and accurate estimation of the clutter covariance matrix (CCM). In practical applications, non-ideal factors are inevitable. STAP performance is affected by many non-ideal factors, such as non-ideal orthogonal waveforms, non-uniform clutter, internal disturbances in sea clutter, elevation fluctuations of ground clutter, differences in scene object categories, and equivalent yaw of the earth's rotation. The existing STAP performance prediction model is no longer accurate. On the one hand, the distance dependence of clutter in complex scenes causes the clutter distribution to usually not satisfy the independent and identically distributed assumption; on the other hand, the non-uniform and non-stationary clutter distribution makes it impossible to accurately estimate the clutter CCM. Therefore, how to establish a STAP performance prediction model that comprehensively considers the above non-ideal factors has become a difficult problem. Summary of the invention

[0003] In order to solve the above problems existing in the prior art, the present invention provides a method for determining and applying a STAP evaluation model for a multi-channel array radar under non-ideal clutter, which can obtain an accurate and applicable STAP performance prediction model for space / air-based radars and carry out relevant applications.

[0004] The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0005] The present invention provides a method for determining a STAP evaluation model under non-ideal clutter of a multi-channel array radar, comprising:

[0006] Determine the multi-channel space-time two-dimensional receiving signal model according to the radar system parameters;

[0007] Based on the multi-channel space-time two-dimensional received signal model, a discrete clutter data vector model of only the spatial dimension of the current unit to be detected under post-Doppler processing is determined. , the discrete clutter data vector model The disturbance component introduced by the non-ideal orthogonal waveform is included ;

[0008] Based on the discrete clutter data vector model , determine the multi-channel data vector model of the non-ideal factors of the current unit to be detected ;

[0009] Multi-channel data vector model based on the non-ideal factors , determine the clutter covariance matrix including non-ideal factors ;

[0010] According to the clutter covariance matrix containing non-ideal factors , determine the STAP clutter suppression weight vector Expression of

[0011] According to the clutter covariance matrix containing non-ideal factors , the STAP clutter suppression weight vector The expression and output SCNR loss model are used to determine the STAP evaluation model under non-ideal factors.

[0012] The present invention also provides a STAP evaluation model application method under non-ideal clutter conditions, comprising:

[0013] Obtain ideal SCNR loss value and initial radar system parameters;

[0014] Taking the ideal SCNR loss value as the target, the initial radar system parameters are iteratively adjusted according to the SCNR loss value output by the STAP evaluation model under the above-mentioned non-ideal factors until the ideal radar system parameters are obtained; wherein the SCNR loss value corresponding to the ideal radar system parameters is the ideal SCNR loss value, or the difference between the SCNR loss value corresponding to the ideal radar system parameters and the ideal SCNR loss value is less than a preset difference.

[0015] The present invention also provides a STAP evaluation model application method under non-ideal clutter conditions, comprising:

[0016] Obtaining radar system parameters to be evaluated;

[0017] The radar system parameters to be evaluated are input into the STAP evaluation model under the above non-ideal factors to obtain the SCNR loss value corresponding to the radar system parameters to be evaluated.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] The present invention takes into account non-ideal factors that can seriously reduce the STAP performance, such as system error, system decorrelation, ground clutter terrain undulation, and internal motion of sea clutter, and then establishes a clutter covariance matrix that can better reflect the actual situation, greatly reduces the impact of the distance dependence of clutter distribution, and determines a more practical and accurate output SCNR loss model to guide the optimization of system parameters and STAP algorithm, which can significantly improve the target detection capability of the system.

[0020] The present invention will be further described in detail below with reference to the accompanying drawings and specific implementation methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flow chart of a method for determining a STAP evaluation model under non-ideal clutter of a multi-channel array radar provided by an embodiment of the present invention;

[0022] Figure 2 is an echo simulation result diagram provided by an embodiment of the present invention;

[0023] Figure 3 is a schematic diagram comparing SCNR loss results under a mixed baseline configuration provided by an embodiment of the present invention;

[0024] Figure 4 It is a schematic diagram of the range-Doppler domain data of clutter of the first channel of echo measured data provided by an embodiment of the present invention;

[0025] Figure 5is an interference phase result diagram between a first channel and a second channel of echo measured data provided by an embodiment of the present invention;

[0026] Figure 6 is an interference phase result diagram between the first channel and the eighth channel of echo measured data provided by an embodiment of the present invention;

[0027] Figure 7 It is a comparative schematic diagram of SCNR loss results based on measured data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0029] Figure 1 FIG. 1 is a flow chart of a method for determining a STAP evaluation model under non-ideal clutter of a multi-channel array radar provided by an embodiment of the present invention, such as Figure 1 As shown, the method includes:

[0030] S101. Determine a multi-channel space-time two-dimensional receiving signal model according to radar system parameters.

[0031] Exemplarily, the radar system parameters may be as shown in Table 1 below:

[0032] Table 1 Radar system parameters

[0033]

[0034] S102, based on the multi-channel space-time two-dimensional received signal model, determining the discrete clutter data vector model of the current unit to be detected in the space domain dimension only under post-Doppler processing , discrete clutter data vector model The disturbance component introduced by the non-ideal orthogonal waveform is included .

[0035] S103, based on discrete clutter data vector model , determine the multi-channel data vector model of the non-ideal factors of the current unit to be detected .

[0036] S104, Multi-channel data vector model based on non-ideal factors , determine the clutter covariance matrix including non-ideal factors .

[0037] S105, based on the clutter covariance matrix containing non-ideal factors , determine the STAP clutter suppression weight vector expression.

[0038] S106, based on the clutter covariance matrix containing non-ideal factors , STAP clutter suppression weight vector The expression and output SCNR loss model are used to determine the STAP evaluation model under non-ideal factors.

[0039] Exemplarily, the above S101 is implemented through steps S1011 to S1016:

[0040] S1011. Determine a transmission signal model according to radar system parameters.

[0041] Here, the array radar has a total of antenna subapertures, and one antenna subaperture is called a node, so there are nodes, each node is used to transmit and receive signals, and each node has channels, and are all positive integers greater than 1. The node used as the reference for implementing coherent processing is called the reference node. Nodes are selected according to actual needs. The transmission signal of the transmitting node The expression is:

[0042] ;

[0043] in, , It is In the pulse radar system, the transmission signal is transmitted once every pulse repetition period, and the time can be It is expressed as: ,in, For slow time, is the current pulse number, is the pulse repetition frequency, For fast time. Whether the transmitted waveform is coherent can divide the multi-channel array radar into phased array mode and MIMO mode. In the phased array mode, the baseband waveform transmitted by each node is consistent, that is, ; In MIMO mode, the baseband waveforms transmitted by each node are orthogonal to each other.

[0044] Assuming that each node of the multi-channel array radar transmits a signal independently, the first node is used as the reference node when transmitting coherent signals and superimposed in the expected area, we can get The combined transmission signal of the transmitting nodes The expression is:

[0045] ;

[0046] in, It is The transmission delay of the transmitting node relative to the transmission path of the clutter scattering unit, It is The delay difference between the transmitting node and the reference node.

[0047] S1012. Determine a single pulse receiving signal model of each channel of each receiving node according to the transmitting signal model.

[0048] Here, for the slope distance The delay from the clutter scattering unit to the first receiving node is . Then the signal is emitted After delay , we can get the first receiving node The first The expression of the pulse receiving signal is:

[0049] ;

[0050] By analogy, Replace with ,in, , Indicates receiving nodes, we can get The receiving node The first Pulse receiving signal The expression is:

[0051] ;

[0052] in, For a slope distance of The clutter scattering unit to the first The delay of the receiving node.

[0053] S1013, use The baseband waveform of each transmitting node is obtained, and the waveform matching pulse compression processing is performed on the single pulse receiving signal model of each channel of each receiving node to obtain the data model of the single pulse receiving signal of each channel of each receiving node after the pulse compression processing.

[0054] Here, you can use (in, ) Perform waveform matching pulse compression processing on the single pulse receiving signal of each channel of each receiving node to obtain a model of the data after the pulse compression processing of the single pulse receiving signal of each channel of each receiving node. For example, using For The receiving node The first After the first pulse receiving signal is processed by waveform matching pulse compression, the The receiving node The first The data after pulse compression processing of the received signal The model is as follows:

[0055] ;

[0056] ;

[0057] in, , represents the complex amplitude of the clutter scattering unit, Indicates The transmitting node The spatial baseline of each channel relative to the reference phase center. For example, when the first node is the reference node, the reference phase center is the spatial baseline of the first channel of the first transmitting node, that is, , For quick time, , is the space cone angle, represents the normalized Doppler frequency, is the platform speed, is the pitch angle, is the azimuth, is the wavelength, yes and In Delay The waveform cross-correlation function when For the The baseband waveform of a transmitting node, For the The baseband waveform of a receiving node, for The conjugation of.

[0058] S1014, integrating the model of the data of the single pulse receiving signal of each channel of each receiving node after pulse compression processing over a fast time to obtain a data model of each channel of each receiving node.

[0059] S1015: each receiving node The data models of the channels are arranged in sequence according to the channel order, and we get dimensional data vector model.

[0060] S1016, will One-to-one correspondence between receiving nodes indivual The dimensional data vector model is arranged in sequence according to the node order to obtain a multi-channel space-time two-dimensional receiving signal model.

[0061] Exemplary, multi-channel space-time two-dimensional received signal model The expression is as follows:

[0062] ;

[0063] in, , Indicates The spatial baseline of the first channel of each receiving node relative to the reference phase center, , Indicates The spatial baseline of the first channel of the transmitting node relative to the reference phase center, for ,and, is the spatial orientation vector, , represents the Kronecker product, is the time domain steering vector, , Indicates delay The corresponding spatial cone angle; , for The conjugation of.

[0064] For the above S102, specifically, the pulse Fourier transform can be used to transform the multi-channel space-time two-dimensional receiving signal model Doppler sharpening is performed to obtain the discrete clutter data vector model of the current unit to be detected in the post-Doppler processing with only the spatial dimension. .

[0065] Exemplary, discrete clutter data vector model The expression is as follows:

[0066] ;

[0067] in, express The corresponding space cone angle is Indicates the number of sampling points, yes The discrete sampling sequence of , , , , .

[0068] Discrete Clutter Data Vector Model The disturbance component introduced by the non-ideal orthogonal waveform is included ,in, , The first term in is the waveform autocorrelation sidelobe response, and the second term is the waveform cross-correlation sidelobe response.

[0069] For the above S103, specifically, the additive thermal noise vector , random vector , and the discrete clutter data vector model The clutter energy in , disturbance component and the spatial orientation vector , determine the multi-channel data vector model of the non-ideal factors of the current unit to be detected , where the random vector The random errors of echo amplitude and / or phase introduced by radar system errors and coherence loss between sub-channels are included. Here, when constructing a multi-channel data vector model with non-ideal factors, When the non-ideal factors are regarded as random terms in the signal model, all non-ideal factors can be attributed to amplitude and phase disturbances, which are added to the discrete clutter data vector model. . Exemplary, non-ideal factor multi-channel data vector model The expression is as follows:

[0070] ;

[0071] ;

[0072] in, , is the additive thermal noise vector, is a random vector, a random vector The random errors of echo amplitude and / or phase introduced by radar system errors and coherence loss between sub-channels are included.

[0073] In some embodiments, the random vector Can be added to the additive thermal noise vector In the multi-channel data vector model, the non-ideal factors The expression is expressed as: ,in, Indicates that a random vector is added The additive thermal noise vector of .

[0074] For the above S104, specifically, the non-ideal factors can be modeled as a random disturbance matrix and added to the ideal clutter covariance matrix, thereby obtaining a clutter covariance matrix including the non-ideal factors: . For example, The expression is as follows:

[0075] ;

[0076] in, It means to find the mathematical expectation. express The conjugate transpose of represents the ideal CCM, represents the disturbance matrix introduced by the non-ideal orthogonal waveform, express The conjugate transpose of is the noise power, is the identity matrix. is the correlation coefficient, represents the perturbation matrix introduced by the system error and the coherence loss between subchannels. Here, the perturbation matrix The expression is as follows:

[0077] ;

[0078] in, represents the correlation coefficient between any channels, , the overall correlation coefficient can be expressed as the product of various influences: ,in: To decorrelate time, represents the echo delay between channels, For the The distance between the channel and the reference channel, For the The distance between the channel and the reference channel, is the platform speed, is the clutter decorrelation time; Decorrelation for geometric or spatial baselines, is the speed of light, For the The effective vertical baseline length of each channel is For the The effective vertical baseline length of each channel is is the radar operating wavelength, is the slant range from the clutter scattering unit to the radar antenna, is the signal bandwidth, is the ground slope, is the pitch angle, is the complementary angle function of the tangent; is the decorrelation caused by topographic relief, is the standard deviation of terrain elevation fluctuation, which obeys Gaussian distribution in actual geographical environment; is the decorrelation caused by thermal noise, which changes with time. is the noise ratio. Since the system channels are consistent, Does not vary with channel.

[0079] The above S105 can be implemented specifically through steps S1051 to S1053:

[0080] S1051, for the clutter covariance matrix containing non-ideal factors Perform eigendecomposition to obtain multiple eigenvalues ​​and multiple eigenvectors corresponding to the multiple eigenvalues.

[0081] Specifically, ,in, , Respectively represent The eigenvalues ​​and The eigenvalues ​​corresponding to the eigenvectors ( ), Represents the total number of decomposed eigenvalues.

[0082] S1052, Select from multiple eigenvalues The largest eigenvalue, and use The largest eigenvalues ​​correspond to The eigenvectors constitute the clutter subspace.

[0083] here, is any positive integer greater than 0; The principle for selecting the largest eigenvalue is: The eigenvalues ​​are sorted from largest to smallest and renumbered. For example, , in order of precedence Satisfaction The characteristic value of .

[0084] Specifically, the clutter subspace The expression is: ,in, express The largest eigenvalues ​​correspond to feature vectors.

[0085] S1053, calculating STAP clutter suppression weight vector according to clutter subspace , and obtain the STAP clutter suppression weight vector expression.

[0086] Specifically, according to the adaptive filtering theory, the STAP optimal weight vector based on the subspace projection theory is It can be expressed as:

[0087] ;

[0088] in, express Along the clutter subspace Projection to clutter orthogonal complement space The projection matrix, For target space orientation, That is ,and, The target radial velocity and platform speed Constructed, and , The value of , express The conjugate transpose of .

[0089] For the above S106, specifically, the clutter covariance matrix containing non-ideal factors is , STAP clutter suppression weight vector Substituting the expression of into the output SCNR loss model, we can get the STAP evaluation model under non-ideal factors. For example, the expression of the STAP evaluation model under non-ideal factors is as follows:

[0090] ;

[0091] ;

[0092] in, represents the SCNR loss value output by the STAP evaluation model under non-ideal factors, represents the noise power, represents the target amplitude, express The conjugate transpose of express The conjugate transpose of For target space orientation, represents the output SCNR loss introduced by non-ideal factor disturbance, represents the sinc function, represents the spatial cone angle difference between the target and the clutter, Indicates The node The spatial baseline of each channel relative to the reference phase center, represents the disturbance energy caused by waveform sidelobe leakage, represents the clutter derivative vector, Indicates wavelength.

[0093] The present invention takes into account non-ideal factors that will seriously reduce the STAP performance, such as system error, system decorrelation, ground clutter terrain undulation, and internal motion of sea clutter, and then establishes a clutter covariance matrix that can better reflect the actual situation, greatly reduces the impact of the distance dependence of clutter distribution, and determines a more practical and accurate output SCNR loss model, which can significantly improve the target detection capability of the system.

[0094] The present invention also provides a method for applying a STAP evaluation model under non-ideal clutter conditions, the method comprising:

[0095] S201, obtaining an ideal SCNR loss value and initial radar system parameters.

[0096] Here, the initial radar system parameters may be initial values ​​of some parameters in Table 1, which is not limited in the present invention.

[0097] S202. Taking the ideal SCNR loss value as the target, the initial radar system parameters are iteratively adjusted according to the SCNR loss value output by the STAP evaluation model under the above-mentioned non-ideal factors until the ideal radar system parameters are obtained; wherein the SCNR loss value corresponding to the ideal radar system parameters is the ideal SCNR loss value, or the difference between the SCNR loss value corresponding to the ideal radar system parameters and the ideal SCNR loss value is less than a preset difference.

[0098] Specifically, the initial radar system parameters can be first substituted into the STAP evaluation model under non-ideal factors to obtain the SCNR loss value corresponding to the initial radar system parameters. Then, based on the difference between the SCNR loss value corresponding to the initial radar system parameters and the ideal SCNR loss value, the initial radar system parameters are adjusted, and the adjusted initial radar system parameters are further input into the STAP evaluation model under non-ideal factors to obtain the SCNR loss value corresponding to the adjusted radar system parameters. The adjustment is iteratively performed until the ideal radar system parameters are obtained. It should be noted that the specific adjustment method is not limited in the present invention and can be determined according to actual needs.

[0099] The present invention also provides a method for applying a STAP evaluation model under non-ideal clutter conditions, the method comprising:

[0100] S301: Obtain radar system parameters to be evaluated.

[0101] Here, the radar system parameters to be evaluated may be some of the parameters in Table 1, which is not limited in the present invention.

[0102] S302: Input the radar system parameters to be evaluated into the STAP evaluation model under the above non-ideal factors to obtain the SCNR loss value corresponding to the radar system parameters to be evaluated.

[0103] Through this method, appropriate radar system parameters can be selected for subsequent clutter suppression and target detection.

[0104] The effect of the present invention is further illustrated by simulation experiments below.

[0105] Simulation experiment 1

[0106] 1. Simulation conditions

[0107] In the simulation experiment of this embodiment, a group of three-node spaceborne MIMO radars were selected, and an orthogonal chirp division multiplexing (OCDM) waveform sequence was used. This group of waveforms was designed by the Multi-CAN method, and its autocorrelation integral side lobe ratio (ISLR) was -3.45dB, and the cross-correlation ISLR was -1.14dB, -1.47dB and -1.28dB respectively. The detailed parameters are shown in Table 2:

[0108] Table 2 Simulation parameters of spaceborne MIMO radar system

[0109]

[0110] 2. Simulation content and result analysis

[0111] Simulation content:

[0112] The STAP evaluation model under non-ideal clutter conditions is determined by using the above-mentioned method for determining the STAP evaluation model under non-ideal factors.

[0113] Result analysis:

[0114] See also Figure 2 , Figure 3 . Specifically, Figure 2 is an echo simulation result diagram provided by an embodiment of the present invention. Figure 2 Figure (a) is a single-channel range-Doppler spectrum. Figure 2 Figure (b) shows the interference phase between nodes. Figure 2Figure (a) shows the range-Doppler domain data of the clutter simulated by the first channel of the first node, with an average clutter-to-noise ratio of approximately 35 dB. Figure 2 Figure (b) shows the interference phase result between the first node and the second node when there is a mixed baseline between satellites. It can be observed that the interference phase in the figure changes along the range gate. This phenomenon indicates that the clutter spatial guidance is distance-dependent. Figure 3 is a schematic diagram comparing SCNR loss results under the mixed baseline configuration provided by an embodiment of the present invention, Figure 3 Figure (a) is a comparison of SCNR loss results under the mixed baseline configuration. The horizontal axis is the normalized Doppler frequency. ), the vertical axis is the output signal-to-noise ratio loss. Figure 3 Figure (b) is a comparison chart of the fitting deviation curves. Figure 3 Figure (a) shows the output SCNR loss curve obtained by the AML method based on simulated clutter data (i.e. Figure 3 The curve corresponding to the "data simulation results" in (a)), the output SCNR loss curve obtained by the traditional STAP performance analysis model (i.e. Figure 3 The curve corresponding to the “traditional SCNR loss analysis model” in (a) of FIG. 1 and the output SCNR loss curve obtained by the STAP performance analysis model proposed in the present invention (i.e. Figure 3 The curve corresponding to the proposed SCNR loss analysis model in (a) of Figure 1). Figure 3 It can be analyzed in Figure (a) that the analysis model proposed by the present invention can better fit the simulation data than the traditional model. The average deviation between the curve obtained by the performance analysis model and the data simulation result curve is defined as the average fitting deviation. Figure 3 Figure (b) shows the fitting deviation curve between the output SCNR loss curve obtained by the traditional STAP performance analysis model and the simulation data (i.e. Figure 3 The curve corresponding to the "traditional SCNR loss analysis model" in (b) of FIG. 1 and the fitting deviation curve of the output SCNR loss curve obtained by the STAP performance analysis model proposed in the present invention and the simulation data (i.e. Figure 3 ), it can be obtained that the average fitting deviation of the traditional STAP performance analysis model is 4.3dB, while the average fitting deviation of the performance analysis model proposed in the present invention is 2.3dB. This result proves that the accuracy of the STAP performance analysis model determined by the present invention is higher than that of the performance analysis model determined by the traditional method.

[0115] Simulation Experiment 2

[0116] 1. Simulation conditions

[0117] In the measured data experiment of this embodiment, an airborne multi-channel array radar is used, and an OCDM waveform sequence is used. This set of waveforms is designed by the Multi-CAN method, and its autocorrelation ISLR is -3.45dB, and the cross-correlation ISLR is -1.14dB, -1.47dB and -1.28dB respectively. The detailed parameters are shown in Table 3:

[0118] Table 3 Airborne multi-channel radar system parameters

[0119]

[0120] 2. Simulation content and result analysis

[0121] Simulation content:

[0122] The STAP evaluation model under non-ideal clutter conditions is determined by using the above-mentioned method for determining the STAP evaluation model under non-ideal factors.

[0123] Result analysis:

[0124] See also Figure 4~Figure 7 . Figure 4~Figure 6 is an echo measurement data result diagram provided by an embodiment of the present invention. Specifically, Figure 4 is the single-channel range-Doppler spectrum, Figure 5 and Figure 6 is the inter-channel interference phase diagram. Figure 4 The range-Doppler domain data of the clutter of the first channel of the echo measurement data is shown, and its average clutter-to-noise ratio is about 35dB. Figure 5 The interference phase result diagram between the first channel and the second channel of the echo measured data is shown. Figure 6 The interference phase result diagram between the first channel and the eighth channel of the echo measured data is displayed. The results show that the non-ideal factors of the actual detection environment lead to serious phase noise in the interference phase of clutter between different channels. As the channel spacing increases, the interference phase noise becomes larger and the channel coherence decreases. Therefore, the accuracy of the model proposed in the present invention is verified.

[0125] Figure 7 is a schematic diagram of the comparison of SCNR loss results under the mixed baseline configuration based on measured data provided by an embodiment of the present invention, Figure 7 Figure (a) is a comparison of SCNR loss results based on measured data, with the horizontal axis being the normalized Doppler frequency. ), the ordinate is the output signal-to-noise ratio loss, Figure 7 Figure (b) is a comparison chart of the fitting deviation curves. Figure 7 Figure (a) shows the output SCNR loss curve obtained based on measured data (i.e. Figure 7The curve corresponding to the "data simulation results" in (a)), the output SCNR loss curve obtained by the traditional STAP performance analysis model (i.e. Figure 7 The curve corresponding to the “traditional SCNR loss analysis model” in (a) of FIG. 1 and the output SCNR loss curve obtained by the STAP performance analysis model proposed in the present invention (i.e. Figure 7 The average deviation between the curve obtained by the performance analysis model and the output SCNR loss curve obtained based on the measured data is defined as the average fitting deviation. Figure 7 Figure (b) shows the fitting deviation curve of the output SCNR loss curve obtained by the traditional STAP performance analysis model and the output SCNR loss curve obtained based on the measured data (i.e. Figure 7 The curve corresponding to the “traditional SCNR loss analysis model” in (b) of FIG. 1 and the fitting deviation curve of the output SCNR loss curve obtained by the STAP performance analysis model proposed in the present invention and the output SCNR loss curve obtained based on the measured data (i.e. Figure 7 ). It can be seen that the average fitting deviation of the traditional STAP performance analysis model is 8.4 dB, while the average fitting deviation of the performance analysis model proposed in the present invention is 4.2 dB. This result proves that the accuracy of the STAP performance analysis model determined by the present invention is higher than that of the performance analysis model determined by the traditional method.

[0126] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0127] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification.

[0128] In the specification, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality of components. Certain measures are recorded in different embodiments, but this does not mean that these measures cannot be combined to produce good effects.

[0129] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A method for determining a STAP evaluation model under non-ideal clutter of a multi-channel array radar, characterized in that: include: Determine the multi-channel space-time two-dimensional receiving signal model according to the radar system parameters; The multi-channel space-time two-dimensional received signal model is subjected to Doppler sharpening processing by pulse Fourier transform to obtain the discrete clutter data vector model y of the current unit to be detected in the space domain dimension only under post-Doppler processing. n , the discrete clutter data vector model y n The disturbance component q introduced by the non-ideal orthogonal waveform is included; According to the additive thermal noise vector v, the random vector e, and the discrete clutter data vector model y n The clutter energy σ, the disturbance component q and the spatial steering vector a r , determine the multi-channel data vector model of the non-ideal factors of the current unit to be detected Wherein, the random vector e contains random errors of echo amplitude and / or phase introduced by radar system errors and coherence loss between sub-channels; Multi-channel data vector model based on the non-ideal factors Determine the clutter covariance matrix R including non-ideal factors cn , R cn The expression is: Among them, E[.] means to find the mathematical expectation, express The conjugate transpose of ; The clutter covariance matrix R containing non-ideal factors cn Performing eigendecomposition to obtain a plurality of eigenvalues ​​and a plurality of eigenvectors corresponding one-to-one to the plurality of eigenvalues; Selecting L largest eigenvalues ​​from the multiple eigenvalues, and using L eigenvectors corresponding to the L largest eigenvalues ​​to form a clutter subspace; Calculate the STAP clutter suppression weight vector w according to the clutter subspace opt , get the STAP clutter suppression weight vector w opt Expression of The clutter covariance matrix R containing non-ideal factors cn , the STAP clutter suppression weight vector w opt Substitute the expression of into the output SCNR loss model to obtain the STAP evaluation model under non-ideal factors.

2. The method for determining the STAP evaluation model under non-ideal clutter of a multi-channel array radar according to claim 1, characterized in that: The multi-channel data vector model of the non-ideal factors The expression is as follows: p=a r ⊙e; Among them, σ represents the clutter energy, a r for a r (ψ s,τ ), a r (ψ s,τ ) is the spatial guidance vector, v is the additive thermal noise vector, e is the random vector, n represents the nth receiving node, n = 1, ..., N, the array radar has a total of N antenna subapertures, one antenna subaperture is called a node, each node is used to transmit and receive signals, and each node has K channels, τ is the fast time, ξ is the discrete sampling sequence of τ, B n,1 represents the spatial baseline of the first channel of the nth receiving node relative to the reference phase center, B i,k represents the spatial baseline of the kth channel of the i-th transmitting node relative to the reference phase center, k = 1, ..., K, B i,1 represents the spatial baseline of the first channel of the i-th transmitting node relative to the reference phase center, ψ s is the spatial cone angle, ψ s,τ represents the spatial cone angle corresponding to the delay τ, represents the complex amplitude of the clutter scattering unit, r in (τ) is g n (t) and g i (t) The waveform cross-correlation function at the time delay τ, g i (t) is the baseband waveform of the i-th transmitting node, g n (t) is the baseband waveform of the nth receiving node, g i The conjugate of (t-τ), τ∈[-T p ,T p ], T P is the pulse width, g n The conjugate of (t-τ), Q represents the number of sampling points, and λ represents the wavelength.

3. The method for determining the STAP evaluation model under non-ideal clutter of a multi-channel array radar according to claim 1, characterized in that: The expression of the STAP evaluation model under the non-ideal factors is as follows: Among them, SCNR Loss (v r ) represents the SCNR loss value output by the STAP evaluation model under the non-ideal factors, represents the noise power, A Tar represents the target amplitude, Indicates w opt The conjugate transpose of Indicates a Tar The conjugate transpose of Tar is the target space orientation, and a Tar for a Tar (v r ), a Tar (v r )=a r (arccos(v r / v a )), and a r for a r (ψ s,τ ), a r (ψ s,τ ) is the spatial orientation vector, v r is the target radial velocity, v a is the platform speed, represents the output SCNR loss introduced by non-ideal factor disturbance, C N is the noise ratio, sinc(.) represents the sinc function, θ = v r / v a -cos(ψ s,0 ) represents the spatial cone angle difference between the target and the clutter. The array radar has a total of N antenna subapertures. One antenna subaperture is called a node. Each node is used to transmit and receive signals, and each node has K channels. B N,K represents the spatial baseline of the Kth channel of the Nth node relative to the reference phase center, C κ represents the disturbance energy caused by the waveform sidelobe leakage, s represents the clutter derivative vector, λ represents the wavelength, ψ s,0 It represents the space cone angle corresponding to τ=0, and τ is the fast time.

4. The method for determining the STAP evaluation model under non-ideal clutter of a multi-channel array radar according to claim 1, characterized in that: Determining a multi-channel space-time two-dimensional receiving signal model according to radar system parameters includes: Determine the transmission signal model according to the radar system parameters; According to the transmission signal model, a single pulse reception signal model of each channel of each receiving node is determined, wherein the array radar has a total of N antenna subapertures, one antenna subaperture is called a node, each node is used for transmitting and receiving signals, and each node has K channels; Using the baseband waveforms of N transmitting nodes, waveform matching pulse compression processing is performed on the single pulse receiving signal model of each channel of each receiving node to obtain the model of the single pulse receiving signal of each channel of each receiving node after pulse compression processing; Integrate the model of the data after pulse compression processing of the single pulse receiving signal of each channel of each receiving node over the fast time to obtain the data model of each channel of each receiving node; Arrange the data models of the K channels of each receiving node in sequence according to the channel order to obtain a 1×K dimensional data vector model; N 1×K-dimensional data vector models corresponding to N receiving nodes are arranged in sequence according to the node order to obtain a multi-channel space-time two-dimensional receiving signal model.

5. A method for applying the STAP evaluation model under non-ideal clutter conditions, characterized in that: include: Obtain ideal SCNR loss value and initial radar system parameters; Taking the ideal SCNR loss value as the target, the initial radar system parameters are iteratively adjusted according to the SCNR loss value output by the STAP evaluation model under the non-ideal factors described in any one of claims 1 to 4 above, until the ideal radar system parameters are obtained; wherein the SCNR loss value corresponding to the ideal radar system parameters is the ideal SCNR loss value, or the difference between the SCNR loss value corresponding to the ideal radar system parameters and the ideal SCNR loss value is less than a preset difference.

6. A method for applying the STAP evaluation model under non-ideal clutter conditions, characterized in that: include: Obtaining radar system parameters to be evaluated; The radar system parameter to be evaluated is input into the STAP evaluation model under the non-ideal factors described in any one of claims 1 to 4 above, to obtain the SCNR loss value corresponding to the radar system parameter to be evaluated.

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