Radar main lobe anti-interference method based on space-time coding and blind source separation

Abstract

The invention discloses a radar main lobe anti-interference method based on space-time coding and blind source separation, and belongs to the field of radar signal processing. The method comprises the following steps: forming a plurality of equivalent phase centers by using space-time coding multiple-input multiple-output, and constructing an array configuration library containing different array configurations; simulating radar echo signals under different array configurations in an array configuration library according to the angle information of the target and interference of the current scene to obtain mixed echo signals corresponding to the different array configurations; separating the mixed echo signal by using a blind source separation algorithm to obtain independent signal components corresponding to different signal sources at a receiving end; and calculating the signal-to-interference ratio of each array configuration according to independent signal components corresponding to different signal sources at the receiving end, and selecting the array configuration with the highest signal-to-interference ratio as the optimal array configuration of the current scene. Therefore, according to the method, the optimal array configuration can be dynamically adjusted according to different interference types and specific environmental conditions, resource waste in an invalid direction is avoided, and the inhibition capability on unknown interference is remarkably enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of radar signal processing, and in particular to a radar main lobe anti-interference method based on space-time coding and blind source separation. Background Art

[0002] With the rapid development of electronic warfare technology, the electromagnetic environment faced by radar systems is becoming increasingly complex and volatile, with increasingly diverse and subtle forms of interference posing a serious threat to radar performance. In recent years, the impact of mainlobe interference (i.e., interference originating from the antenna's main lobe) on radar performance has become a hot topic, while research on sidelobe interference is relatively mature. In the sidelobe region, adaptive beamforming algorithms effectively suppress interfering signals by nulling them in the direction of the interference. However, when interference enters from the antenna's mainlobe, its spatial signature is highly similar to that of the target signal, rendering traditional sidelobe suppression methods virtually ineffective. Deceptive mainlobe interference, in particular, not only leads to erroneous target parameter measurements and false target tracking but can also cause radar system failure or even damage. Therefore, effectively suppressing mainlobe interference has become a critical issue in the field of radar anti-interference.

[0003] When traditional blind source separation (BSS) technology deals with complex interference environments, its anti-interference performance will be significantly reduced due to the increase in the number of interference sources and the decrease in spatial resolution between source signals. Summary of the Invention

[0004] This invention provides a radar mainlobe anti-interference method based on space-time coding and blind source separation. Space-time coding expands the number of virtual apertures, significantly increasing the system's spatial degrees of freedom and enhancing blind source separation. Furthermore, an adaptive array selection mechanism is introduced to dynamically adjust the optimal array configuration based on different interference types and specific environmental conditions. This not only avoids wasting resources in ineffective directions but also significantly enhances the ability to suppress unknown interference.

[0005] An embodiment of the present invention provides a radar mainlobe anti-interference method based on space-time coding and blind source separation, comprising the following steps:

[0006] Utilize space-time coding multiple transmission and multiple reception to form multiple equivalent phase centers and build an array configuration library containing different array configurations;

[0007] Simulating radar echo signals under different array configurations in the array configuration library according to target and interference angle information of the current scene to obtain mixed echo signals corresponding to different array configurations;

[0008] The blind source separation algorithm is used to separate the mixed echo signals corresponding to different array configurations to obtain the independent signal components corresponding to different signal sources at the receiving end;

[0009] The signal-to-interference ratio of each array configuration is calculated based on the independent signal components corresponding to different signal sources at the receiving end, and the array configuration with the highest signal-to-interference ratio is selected as the optimal array configuration for the current scenario.

[0010] Optionally, in one embodiment of the present invention, multiple transmission and multiple reception are used to form multiple equivalent phase centers, and an array configuration library containing different array configurations is constructed, including:

[0011] Multiple transmitting antennas and receiving antennas are deployed using multiple-input multiple-output technology to form multiple equivalent phase centers. The array configuration library is constructed using the different array configurations obtained.

[0012] Optionally, in one embodiment of the present invention, a blind source separation algorithm is used to separate mixed echo signals corresponding to different array configurations, including:

[0013] The received mixed signal is centered and whitened, wherein the centering process ensures that the mean of the signal is zero, and the whitening process selects a whitening matrix so that the covariance matrix becomes a unit matrix;

[0014] Calculate the fourth-order cumulant matrix and use the fourth-order cumulant matrix to construct multiple covariance matrices;

[0015] A set of orthogonal matrices is found so that the covariance matrix is ​​diagonalized after diagonalization, and the mixed signal is linearly transformed using the separation matrix to obtain the source signal after separation of the mixed echo signals corresponding to different array configurations.

[0016] Optionally, in one embodiment of the present invention, calculating the signal-to-interference ratio of each array configuration based on independent signal components corresponding to different signal sources at the receiving end includes:

[0017]

[0018] Among them, P signal is the target signal power, P interference is the interference signal power.

[0019] The radar mainlobe anti-interference method based on space-time coding and blind source separation in this embodiment of the present invention introduces an adaptive array selection mechanism that dynamically adjusts the optimal array configuration based on different interference types and specific environmental conditions. This not only avoids wasting resources in invalid directions but also significantly enhances the ability to suppress unknown interference. This method effectively improves blind source separation and enhances the radar system's anti-interference capabilities in complex interference environments, providing a new solution for radar anti-interference technology.

[0020] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0022] Figure 1 A flowchart of a radar mainlobe anti-interference method based on space-time coding and blind source separation according to an embodiment of the present invention;

[0023] Figure 2 JADE-based blind source separation flow chart of an embodiment of the present invention;

[0024] Figure 3 (a) is a schematic diagram of array configuration 1;

[0025] Figure 3 (b) is a schematic diagram of array configuration 2;

[0026] Figure 3 (c) is a schematic diagram of array configuration 3;

[0027] Figure 4 It is a typical scene geometric relationship model;

[0028] Figure 5 Schematic diagram of the framework selected for the configuration;

[0029] Figure 6 (a) is a schematic diagram of pulse compression before interference suppression;

[0030] Figure 6 (b) is the result of blind source separation based on interference suppression of configuration 1;

[0031] Figure 6 (c) is the result of blind source separation based on interference suppression of configuration 2. DETAILED DESCRIPTION

[0032] The following describes embodiments of the present invention in detail, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and are not to be construed as limiting the present invention.

[0033] Figure 1 The present invention provides a flow chart of a radar mainlobe anti-interference method based on space-time coding and blind source separation according to an embodiment of the present invention.

[0034] like Figure 1 As shown, the radar main lobe anti-interference method based on space-time coding and blind source separation includes the following steps:

[0035] Step S101: using space-time coded multiple transmission and multiple reception to form multiple equivalent phase centers, and constructing an array configuration library containing different array configurations.

[0036] In an embodiment of the present invention, multiple transmitting antennas and receiving antennas are deployed using the multiple-input multiple-output technology to form multiple equivalent phase centers, and an array configuration library is constructed using the obtained different array configurations.

[0037] It can be understood that space-time coding multiple transmission and multiple reception is used to generate more equivalent phase centers, thereby virtually expanding the array aperture and establishing an array configuration library containing a variety of possible array configurations. These configurations are based on different antenna arrangements and combinations and are designed to cover various potential interference environments.

[0038] Step S102 , simulating radar echo signals under different array configurations in the array configuration library according to the angle information of the target and interference in the current scene, and obtaining mixed echo signals corresponding to the different array configurations.

[0039] Based on the constructed array configuration library, the radar echo signal under each array configuration is simulated.

[0040] Step S103 : Separate the mixed echo signals corresponding to different array configurations using a blind source separation algorithm to obtain independent signal components corresponding to different signal sources at the receiving end.

[0041] The simulated mixed echo signal is processed using a blind source separation algorithm to separate the different signal sources. In this step, the algorithm does not rely on prior information about the signal source or the transmission channel, but only uses the statistical characteristics of the signal to achieve separation.

[0042] In an embodiment of the present invention, a blind source separation algorithm is used to separate mixed echo signals corresponding to different array configurations, including:

[0043] The received mixed signal is centered and whitened, wherein the centering process ensures that the mean of the signal is zero, and the whitening process selects a whitening matrix so that the covariance matrix becomes a unit matrix;

[0044] Calculate the fourth-order cumulant matrix and use the fourth-order cumulant matrix to construct multiple covariance matrices;

[0045] A set of orthogonal matrices is found so that the covariance matrix is ​​diagonalized after diagonalization, and the mixed signal is linearly transformed using the separation matrix to obtain the source signal after separation of the mixed echo signals corresponding to different array configurations.

[0046] Step S104 , calculating the signal-to-interference ratio of each array configuration based on the independent signal components corresponding to different signal sources at the receiving end, and selecting the array configuration with the highest signal-to-interference ratio as the optimal array configuration for the current scenario.

[0047] For each array configuration, the signal-to-interference ratio (SIR) of the separated signals is calculated to quantify the effectiveness of each configuration in suppressing interference. The SIRs corresponding to all array configurations are compared, and the configuration with the highest SIR is selected as the optimal array configuration for the current environment.

[0048] In an embodiment of the present invention, calculating the signal-to-interference ratio of each array configuration based on independent signal components corresponding to different signal sources at the receiving end includes:

[0049]

[0050] Among them, P signal is the target signal power, P interference is the interference signal power.

[0051] The radar main lobe anti-interference method based on space-time coding and blind source separation proposed by the present invention is described in detail below with reference to the accompanying drawings.

[0052] Without loss of generality, embodiments of the present invention consider a phased array pulse compression radar model, where the transmitted signal is an LFM pulse signal and the noise environment is additive noise n(k). To effectively separate the target echo and the interference signal, the blind source separation (BSS) algorithm typically requires the use of multiple channels to receive the mixed signal. Specifically, the number of required receiving channels should be greater than or equal to the total number of targets and interference sources (denoted as L), that is, N>L, where N is the number of receiving sensors.

[0053] Assuming that the source signals are independent of each other, under the condition of instantaneous linear mixing, the received digital mixed signal model can be expressed as:

[0054] X(t)=As(t)+n(t)

[0055] Where X(t), s(t), and n(t) represent the observation matrix, source signal, and system noise, respectively. A is the mixing matrix, representing the transmission characteristics from each source to the receiving channel, namely:

[0056]

[0057] To make the blind separation problem solvable, the linear instantaneous blind separation model generally makes the following assumptions: first, the components of the source signal vector x(t) are statistically independent; second, at most one source signal component follows a Gaussian distribution; third, the mixing matrix A has full column rank. If the mixing matrix does not have full column rank, not all source signal components can be recovered; and fourth, the mean of each source signal vector is zero, and at most one source signal component is Gaussian.

[0058] The blind source separation algorithm does not require the maximum point of the main beam to point to the target or interference direction. As long as there is a difference between the target and interference directions, its main purpose is to use the observation vector x(t) to find a separation matrix W so that WA = PJ, thereby obtaining the source signal estimation vector and realizing signal identification and separation:

[0059] y(t)=Wx(t)=WAs(t)=PJs(t)

[0060] Where P is the permutation matrix and J is the diagonal matrix.

[0061] Blind source separation (BSS) aims to recover the original independent source signals from a mixed signal without prior knowledge of the channel characteristics or specific information about the source signals. BSS algorithms based on joint diagonalization of matrices, particularly the classic JADE (Joint Approximate Diagonalization of Eigenmatrices) algorithm, have demonstrated significant advantages in handling complex signal environments and are particularly well-suited for mainlobe interference suppression in radar systems.

[0062] The classic JADE blind separation algorithm is used to separate the received mainlobe interference mixed signal. According to the general practice of blind source separation, the first step is to perform data preprocessing on the received mixed signal, including centralization to ensure that the mean of the signal is zero, and whitening, that is, linear transformation of the observed signals so that they have unit variance and are independent of each other; the second step is to calculate their fourth-order cumulant matrices, which contain information about the independence of the source signals; the third step is to use the fourth-order cumulants to construct a series of covariance matrices, which reflect the statistical characteristics of the source signals in the mixing process; the fourth step is to jointly diagonalize, that is, find a set of orthogonal matrices so that the above covariance matrices are as diagonal as possible after diagonalization; finally, the found separation matrix is ​​used to perform linear transformation on the mixed signal to obtain the separated source signal.

[0063] The algorithm flow is as follows Figure 2 As shown. The whitening preprocessing process is to select a matrix W so that the covariance matrix becomes the unit matrix I. The role of whitening is to achieve the purpose of data dimensionality reduction on the one hand, and to eliminate noise and reduce the correlation between signals on the other hand. The received observation matrix X is whitened using the whitening matrix to obtain the spatial whitening matrix Z:

[0064] Z=WX=W(HS+N)=US+WN

[0065] Among them, the unitary matrix U = WH, W is the whitening matrix. In order to restore the source signal S, the unitary matrix U must be calculated. If U is an M-dimensional ordinary matrix, the blind source separation algorithm needs to estimate M2 parameters, and when it is a unitary matrix, only M(M-1) / 2 parameters need to be estimated. It can be seen that the whitening process greatly reduces the complexity of the calculation.

[0066] Therefore, we first find the fourth-order cumulant matrix of the whitened signal, where Q Z (T) The (i,j)th element is defined as:

[0067]

[0068] Where 1<i,j<p, T is any non-zero p×p matrix, (T) lk is the (l,k)th element, and cum(.) is the fourth-order cumulant operation.

[0069] Q Z (T) Perform eigendecomposition to obtain the estimate V of the unitary matrix U:

[0070] Q Z (T)=VΣV H

[0071] By performing blind source separation on the received signal, the estimated source signal can be obtained as:

[0072] S=V H WX.

[0073] Traditional uniform planar arrays use a 4×4 physical antenna layout (Configuration 1), achieving symmetric beamforming in elevation and azimuth through regular arrangement. To further increase the number of channels in the system, this paper introduces multiple-input multiple-output (MIMO) technology. By deploying multiple transmit and receive antennas, MIMO can generate more equivalent phase centers, thereby virtually expanding the array aperture. After waveform separation, the echo of the signal from the mth transmit channel obtained by the nth receive channel can be expressed as:

[0074]

[0075] Among them, γ0∈C is the backscatter coefficient of the target, r0 represents the distance from the radar to the target, θ0 represents the line of sight deviation angle of the target, c represents the speed of light, f0 represents the carrier frequency, d T and d R Represents the distance between the transmitting channel and the receiving channel respectively.

[0076] By applying MIMO technology, the following array configuration can be obtained. The array configuration diagram is as follows: Figure 3 As shown in (a), (b), and (c), Figure 3 (a) is a schematic diagram of array configuration 1, Figure 3 (b) is a schematic diagram of array configuration 2, Figure 3(c) is a schematic diagram of array configuration 3.

[0077] Specifically, for a 4-transmitter, 16-receiver MIMO architecture, two virtual arrays can be constructed: 1) When the transmit antennas are arranged in elevation, the equivalent phase center expands to seven channels in the azimuth dimension, forming a 4 (elevation) × 7 (azimuth) configuration (Configuration 2); 2) When the transmit antennas are distributed in azimuth, the number of equivalent elevation channels increases to seven, forming a 7 (elevation) × 4 (azimuth) configuration (Configuration 3). Compared to current single-input, multiple-output (SIMO) systems, MIMO architectures offer more spatial degrees of freedom.

[0078] In complex electromagnetic environments, radar systems need to select the most appropriate array configuration according to different application scenarios to ensure efficient anti-interference capabilities. Based on the Blind Source Separation (BSS) technology, this paper explores a specific implementation plan in a typical scenario, aiming to optimize array resource allocation and improve the separation effect of target signals. The typical scenario diagram is shown below. Figure 4 shown.

[0079] In this scenario, assume that the actual target and the jammer differ significantly in both elevation and azimuth. In this case, an array that relies solely on a single dimension (e.g., elevation or azimuth) cannot effectively distinguish between the target and the jammer, making it difficult to determine the optimal array configuration. To address this issue, a multi-dimensional evaluation method is proposed, ensuring the selection of the optimal configuration through a systematic process.

[0080] The schematic diagram of the configuration selection framework is as follows Figure 5As shown. First, parameter estimation is performed to obtain the angle information of the target and interference. An array configuration library is constructed, and three different array configurations are selected for parallel evaluation at the same time to simulate and generate mixed echoes of different array configurations. Subsequently, pulse compression technology is used to enhance the signal to increase the target echo signal strength and reduce the influence of clutter and noise, thereby improving the subsequent separation effect. Next, blind source separation (BSS) technology is used to decompose the mixed signal into original signal components, providing a pure data source for signal-to-interference ratio (SIR) calculation. For each array configuration, the system calculates its SIR value and records the value for subsequent comparison. Once all array configurations have been fully evaluated, the final configuration selection stage is entered. At this stage, the system compares the SIR values ​​of each configuration and selects the configuration with the highest signal-to-interference ratio as the optimal configuration. The optimization method based on signal-to-interference ratio can not only ensure that the selected configuration performs best in terms of signal quality, but also effectively cope with the challenge of target identification in complex electromagnetic environments. In addition, this method has high environmental adaptability and is suitable for a variety of application scenarios.

[0081] The overall framework of configuration selection is as follows Figure 5 The figure shows the complete process from initial configuration selection to final optimal configuration determination. Through this method, the system can accurately identify and optimize the array configuration in complex electromagnetic environments, ensuring efficient and reliable signal processing.

[0082] The three source signals used are LFM pulse signal, range deception jammer and Gaussian white noise. The parameters used in the simulation experiment are shown in Table 1.

[0083] Table 1 Main parameters involved in simulation data

[0084]

[0085] Simulations were conducted to evaluate the blind source separation performance of three different array configurations. These configurations included: Configuration 1, a traditional array configuration consisting of a single transmitter and 16 receivers with four channels in elevation and four channels in azimuth; Configuration 2, an equivalent array configuration consisting of four transmitters and 16 receivers with four channels in elevation and seven channels in azimuth; and Configuration 3, a configuration consisting of seven channels in elevation and four channels in azimuth. During the experiments, a blind source separation algorithm was applied to each configuration, and the signal-to-interference ratio (SIR) was calculated for each configuration. By comparing the performance differences between the configurations, the optimal solution was selected for further research or application.

[0086] Figure 6 The separation results before and after anti-interference are shown. Figure 6 (a) is a schematic diagram of pulse compression before interference suppression. Figure 6 (b) is the result of blind source separation based on interference suppression of configuration 1. Figure 6 (c) is the result of blind source separation based on interference suppression of configuration 2. As can be seen from the figure, the original signal contains the target signal and the interference signal. The existence of the interference signal makes it difficult to clearly identify the target signal. By observing Figure 6 As can be seen in each subgraph, the blind source separation based on the traditional array is limited, and a significant interference signal is still visible. However, the blind source separation results of Configuration 2, which uses MIMO technology to increase the degree of freedom, show only a single peak signal, indicating that the target signal is successfully separated after anti-interference processing.

[0087] In order to evaluate the impact of different array configurations on the blind source separation effect, a simulation experiment was conducted on scenario three, and the results are shown in Table 2 below.

[0088] Table 2 Separation signal-to-interference ratio under different array configurations

[0089]

[0090] The experimental results show that the true target and jammer have inconsistent elevation angles, and simulation experiments indicate that Configuration 2 is the optimal array configuration. Compared to the traditional 1-transmitter, 16-receiver array configuration, the use of MIMO (Multiple Input, Multiple Output) technology significantly enhances blind source separation. By providing more degrees of freedom, generating additional equivalent phase centers, and optimizing the array configuration, the signal-to-interference ratio after separation is increased by approximately 10dB. This choice not only maximizes the advantages of MIMO technology, but also further improves the effectiveness of blind source separation and the system's anti-interference capabilities.

[0091] The radar mainlobe anti-interference method based on space-time coding and blind source separation proposed in an embodiment of the present invention uses space-time coding to expand the number of virtual apertures, significantly increasing the system's spatial degrees of freedom and improving blind source separation. An adaptive array selection mechanism is introduced to dynamically adjust the optimal array configuration based on different interference types and specific environmental conditions. This not only avoids wasting resources in invalid directions but also significantly enhances the ability to suppress unknown interference.

[0092] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials 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 expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples without contradiction.

[0093] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "N" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0094] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or N executable instructions for implementing a custom logical function or step of a process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

Claims

1. A radar main lobe anti-interference method based on space-time coding and blind source separation, characterized in that: The following steps are involved: Utilize space-time coding multiple transmission and multiple reception to form multiple equivalent phase centers and build an array configuration library containing different array configurations; Simulating radar echo signals under different array configurations in the array configuration library according to target and interference angle information of the current scene to obtain mixed echo signals corresponding to different array configurations; The blind source separation algorithm is used to separate the mixed echo signals corresponding to different array configurations to obtain the independent signal components corresponding to different signal sources at the receiving end; The signal-to-interference ratio of each array configuration is calculated based on the independent signal components corresponding to different signal sources at the receiving end, and the array configuration with the highest signal-to-interference ratio is selected as the optimal array configuration for the current scenario.

2. The method according to claim 1, characterized in that By using space-time coding multiple transmission and multiple reception to form multiple equivalent phase centers, an array configuration library containing different array configurations is constructed, including: Multiple transmitting antennas and receiving antennas are deployed using multiple-input multiple-output technology to form multiple equivalent phase centers, and an array configuration library is constructed using the obtained different array configurations.

3. The method according to claim 1, characterized in that The blind source separation algorithm is used to separate the mixed echo signals corresponding to different array configurations, including: The received mixed signal is centered and whitened, wherein the centering process ensures that the mean of the signal is zero, and the whitening process selects a whitening matrix so that the covariance matrix becomes a unit matrix; Calculate the fourth-order cumulant matrix and use the fourth-order cumulant matrix to construct multiple covariance matrices; A set of orthogonal matrices is found so that the covariance matrix is ​​diagonalized after diagonalization, and the mixed signal is linearly transformed using the separation matrix to obtain the source signal after separation of the mixed echo signals corresponding to different array configurations.

4. The method according to claim 1, wherein The signal-to-interference ratio of each array configuration is calculated based on the independent signal components corresponding to different signal sources at the receiving end, including: Among them, P signal is the target signal power, P interference is the interference signal power.

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