Clutter interference suppression method based on sub-band processing

Abstract

The invention discloses an interference suppression method, and particularly relates to a clutter interference suppression method based on sub-band processing, and the method comprises the following steps: S1, receiving a monitoring signal containing a target reflection echo, a direct wave and a clutter, and a relatively pure direct wave reference signal; s2, respectively converting the monitoring signal and the reference signal from a time domain to a frequency domain; s3, uniformly dividing the converted frequency domain monitoring signal and the converted frequency domain reference signal into a plurality of sub-bands respectively; s4, in each sub-band, performing clutter suppression processing on the sub-band monitoring signal based on the sub-band reference signal so as to eliminate clutter components related to the reference signal and retain a moving target signal; s5, synthesizing all the signals after sub-band processing according to a frequency band sequence to obtain a monitoring signal after full-band clutter suppression; and S6, performing coherent processing on the synthesized monitoring signal and the reference signal to realize target detection and parameter estimation.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a clutter interference suppression method based on subbanding processing. Background Technology

[0002] External radiation source radar utilizes signals from third-party, non-cooperative illumination sources such as broadcasts and communications for target detection, offering advantages such as good concealment, low cost, and abundant spectrum resources. However, effectively suppressing strong clutter interference from direct waves, multipath reflections, and stationary objects in the environment has always been a core technical challenge limiting its detection performance during real-time signal processing. The presence of strong clutter severely masks the echoes of weak moving targets, leading to a decrease in target detection probability and an increase in false alarm rate.

[0003] To address clutter suppression, existing technologies mainly revolve around two types of methods: one is based on spatial filtering, using an array antenna to form beam nulls aligned with the clutter direction. However, this method requires high array calibration and struggles to handle clutter with a wide distribution range. The other is based on time / frequency domain signal processing, typically including extended cancellation algorithms and their improved versions. These algorithms construct a correlation matrix between the reference signal and the monitoring signal to perform clutter subspace estimation and cancellation in the signal domain, and are currently the mainstream approach in engineering applications.

[0004] However, with the continuous increase in radar signal bandwidth and the increasing complexity of clutter scenarios in real-world environments, traditional ECA-like methods face severe challenges. First, wideband signals imply high range resolution, but also cause clutter to expand in the range dimension, significantly increasing the degrees of freedom. To accurately estimate and suppress such high-degree-of-freedom clutter, a high-dimensional clutter subspace needs to be constructed and complex matrix operations performed, leading to a sharp increase in computational and storage requirements, making it difficult to meet real-time processing requirements. Second, in dense clutter backgrounds, the suppression performance of traditional methods may decline due to inaccurate factor space estimation, and residual clutter can still affect target detection.

[0005] Therefore, there is an urgent need for a robust clutter suppression technique that can significantly reduce computational complexity while maintaining clutter suppression depth, and is applicable to broadband signals and complex clutter environments. This invention is proposed against this background. Summary of the Invention

[0006] In order to solve the problems existing in the prior art, the present invention provides a clutter interference suppression method based on subbanding processing to solve the current technical problems.

[0007] The technical solution adopted by this invention to solve its technical problem is:

[0008] This invention provides a clutter interference suppression method based on subbanding processing, comprising the following steps:

[0009] S1: Receives monitoring signals containing target reflected echoes, direct waves and clutter, as well as a relatively clean direct wave reference signal;

[0010] S2: Convert the monitoring signal and the reference signal from the time domain to the frequency domain respectively;

[0011] S3: Divide the converted frequency domain monitoring signal and frequency domain reference signal into multiple sub-bands evenly;

[0012] S4: Within each sub-band, based on the sub-band reference signal, clutter suppression processing is performed on the sub-band monitoring signal to remove clutter components related to the reference signal and retain the moving target signal;

[0013] S5: Combine all sub-band processed signals in frequency band order to obtain the full-band clutter suppressed monitoring signal;

[0014] S6: Perform coherent processing on the synthesized monitoring signal and the reference signal to achieve target detection and parameter estimation.

[0015] Preferably, in step S4, the clutter suppression processing within each sub-band specifically includes:

[0016] S41: Construct clutter subspace based on the reference signal of the current subband;

[0017] S42: Estimate the projection weights of the sub-band monitoring signal onto the clutter subspace;

[0018] S43: Subtract the clutter estimation component, which is composed of the reference signal and the projection weight, from the sub-band monitoring signal.

[0019] Preferably, the clutter subspace is composed of the reference signal spectrum vector of the current subband.

[0020] Preferably, in step S3, the number and width of sub-band divisions are dynamically adjusted based on the total bandwidth of the original signal, the system distance resolution requirements, or the intensity of environmental clutter.

[0021] Preferably, before performing step S4, the amplitude and phase of the sub-band reference signal are further calibrated to match the channel characteristics of the sub-band monitoring signal.

[0022] The beneficial effects of this invention are:

[0023] It exhibits excellent clutter suppression performance, particularly suitable for dense and complex clutter environments: by dividing the broadband signal into multiple sub-bands for processing, the originally widely distributed static or slowly varying clutter in each sub-band degenerates into a single degree of freedom at reduced resolution, thus enabling efficient and accurate estimation and elimination. Even when facing large-scale, widely distributed dense clutter, it can achieve deep suppression and significantly reduce clutter background power.

[0024] The algorithm exhibits low complexity and low resource consumption: core processing is performed independently within each narrow subband, resulting in a low-dimensional clutter subspace that significantly simplifies the computational and storage requirements for weight coefficient estimation and projection operations. This makes the method easy to implement in real-time digital signal processing systems, reducing hardware costs and power consumption.

[0025] Effective preservation of moving target information: Based on the orthogonality between the target signal spectrum and the clutter / reference signal spectrum within the sub-band, clutter cancellation is performed using the orthogonal projection concept. This can accurately remove clutter components while maximizing the preservation of the echo energy of moving targets with different Doppler frequency shifts, thereby improving the output signal-to-noise ratio and signal-to-clutter ratio of the target signal.

[0026] It exhibits strong adaptability and high flexibility: the width and number of subbands can be dynamically adjusted according to the actual clutter environment, signal bandwidth, and system performance requirements, achieving adaptive processing. When facing clutter with different characteristics or intensities, the suppression effect can be optimized by adjusting the subband parameters, improving the robustness and applicability of the method.

[0027] Easy to integrate and implement in engineering: The method has a clear process and modular steps, making it easy to integrate into existing external radiation source radar signal processing frameworks. The hardware platform it relies on consists of common radar system components, requiring no special equipment, which facilitates technology portability and engineering applications.

[0028] Supports performance expansion and optimization: By introducing auxiliary measures such as sub-band channel equalization and iterative filtering, system errors can be further calibrated and residual clutter can be suppressed, thus maintaining stable and efficient clutter suppression performance under various non-ideal conditions. Attached Figure Description

[0029] The above-described 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:

[0030] Figure 1 This is a schematic diagram of a clutter interference suppression method based on subbanding processing according to an embodiment of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] In order to achieve robust complex clutter suppression performance, this invention proposes a clutter interference suppression method based on subbanding processing (ECA-FB). The flowchart of the processing method is shown below, including: (1) Subbanding: the received signal is evenly segmented in the frequency domain to form subband signals; (2) Frequency domain ECA processing: the ECA complex clutter weight coefficient is estimated in each subband; (3) Subband synthesis: the clutter-removed subband echo signal is broadband synthesized, and the time-varying clutter is removed by subband repartitioning.

[0033] First, the monitoring and reference signals are transformed, and their frequency domain results are shown below:

[0034]

[0035] ,

[0036] in, For the frequency domain sampling form of the illumination source signal, g=1, N represents the normalized Doppler unit, which corresponds one-to-one with the spectral components of the actual signal; Indicates the time delay of the i-th clutter scatterer The corresponding normalized distance unit, , and They represent the first and second parts of the monitoring signal, respectively. Each reflection target corresponds to a normalized distance. , .

[0037] ,

[0038] Secondly, and The bandwidth is evenly divided into... Subbands, where the original signal bandwidth is B, each subband contains With a sampling point, the subband form of the received signal can be written as:

[0039] ,

[0040] ,

[0041] In the formula, l = 1, 2, L; g=1, 2, NL, where L represents the number of subbands; furthermore, since direct waves and stationary clutter have similar sidelobe effects, when When, the first term on the right side of the equation represents the direct wave component.

[0042] In external radiation source radar signal processing, the radar's range resolution is inversely proportional to the signal's modulation bandwidth, denoted as:

[0043] ,

[0044] Where c represents the speed of light. It is the angle between two bases.

[0045] As shown in the above equation, subbanding coarsens the range resolution of the original signal. Therefore, the range resolution of each narrowband signal after subbanding is expressed as follows:

[0046] .

[0047] When the received signal has a sufficient number of segments in the frequency domain, such that within the sub-band... When the coverage area exceeds the maximum distribution distance of clutter, the degree of freedom of stationary clutter within each subband will degenerate to 1. This means that all clutter responses in the monitoring signal can be considered as copies of the direct wave signal after amplitude attenuation. Therefore, the impact of clutter on all frequency components within the same subband can be considered identical. Thus, the monitoring signal of the l-th subband can be further rewritten as:

[0048] .

[0049] As can be observed from the above formula, the spectrum of each subband... Multipath effects exist independently of clutter. Therefore, the contribution of the clutter sequence in the monitoring signal to each frequency component within the same subband can be combined into a single contribution only with clutter. The relevant complex amplitude. Furthermore, the Doppler effect caused by target motion alters the spectrum of the target echo signal. and Orthogonal.

[0050] Therefore, the orthogonal projection concept of ECA can be used to effectively suppress clutter within the sub-band, as shown in the following results:

[0051] ,

[0052] in Sub-band monitoring signal The projected subspace, due to the 1-degree-of-freedom constraint of the stationary clutter, Equivalent to sub-band reference signal Only by Composed of 3D vectors, specifically in the form of:

[0053] .

[0054] In summary, ECA-FB can achieve highly efficient clutter suppression with minimal computational and storage overhead, especially for large-scale, dense clutter distributed over a wide area. Finally, subband synthesis is performed on the clutter-suppressed monitoring signal. and through formula By completing the coherent accumulation of the target echo signal, its range and velocity information are obtained.

[0055] The implementation of the method described in this invention relies on a common external radiation source radar system hardware platform, including a monitoring antenna, a reference antenna, a radio frequency receiving channel, an analog-to-digital converter, and a digital signal processing unit. The following detailed description, using a typical implementation flow as an example, illustrates the specific embodiments of this invention in detail. This description is sufficient to enable those skilled in the art to understand and implement this invention without inventive effort.

[0056] First, the system initializes and receives signals. The monitoring antenna receives a mixed signal containing target reflected echoes, direct waves, and various types of clutter interference, while the reference antenna receives a relatively clean direct wave signal as a reference. Both signals are amplified, mixed, and filtered through independent receiving channels, then converted into digital signals by an analog-to-digital converter and sent to a digital signal processor.

[0057] The first step is to perform frequency domain transformation and subband division. Windowing and Fast Fourier Transform are applied to both digital signals to transform them from the time domain to the frequency domain. Next, the resulting entire frequency spectrum is uniformly divided into several continuous, narrower subbands. For example, if the total bandwidth is 8 MHz, it can be uniformly divided into 16 subbands, each with a width of 500 kHz. This step is equivalent to decomposing the original broadband signal into multiple parallel narrowband signals for processing.

[0058] The second step involves independent clutter suppression within each sub-band. This is the core of the method. As the bandwidth of each sub-band narrows, its corresponding range resolution decreases. When the sub-band is sufficiently narrow, all stationary or slowly varying clutter components within it appear spectrally as highly similar copies to the reference signal spectrum within the current sub-band, with the main difference being a complex amplitude and phase factor. Based on this characteristic, within each sub-band, the components of the monitoring signal related to the reference signal are considered as a clutter subspace. By calculating the projection relationship between the reference signal and the monitoring signal in that sub-band, an optimal complex weighting coefficient is estimated. Then, the reference signal is multiplied by this coefficient, and the result is subtracted from the monitoring signal, thereby effectively eliminating direct waves and static clutter components within that sub-band while retaining moving target signals with different Doppler shifts.

[0059] The third step is to synthesize the results of all sub-band processing. Each narrowband sub-band signal, after clutter suppression, is reassembled according to its original frequency band order to restore a complete broadband spectrum. This step ensures that the overall bandwidth and resolution of the signal are reconstructed.

[0060] The fourth step involves target detection and parameter extraction. The synthesized, clutter-suppressed monitoring signal is coherently processed with the reference signal, for example, through mutual ambiguity function calculation or matched filtering, to achieve a two-dimensional joint search in the range and Doppler dimensions. Because clutter is pre-suppressed, the peak value of the moving target can be clearly distinguished from the background in this step, thus allowing for accurate estimation of the target's range and velocity information.

[0061] To further improve performance, the following optimization measures can be introduced in the specific implementation:

[0062] Adaptive subband partitioning: The width and number of subbands are dynamically adjusted based on real-time ambient noise and clutter intensity. Narrower subbands are used in clutter-intensive regions to improve suppression accuracy.

[0063] Iterative filtering: The quality of the output signal after one processing is evaluated. If strong residual noise is still found, the residual part can be subbanded again to suppress it, forming a two-stage or multi-stage filtering structure.

[0064] Channel equalization: In practical systems, there may be slight differences in the characteristics of the monitoring and reference channels. Before sub-band processing, the amplitude and phase of the reference signal in each sub-band can be calibrated to match the characteristics of the monitoring channel and improve the accuracy of clutter cancellation.

[0065] For example, when the system uses digital television broadcast signals as the external radiation source, its bandwidth is 7.61 MHz. During processing, this bandwidth is divided into 32 sub-bands, each approximately 238 kHz wide. Within each sub-band, the aforementioned projection method is used to estimate and suppress clutter. Verification has shown that this setup can reduce background clutter power by more than 20 dB in strong urban clutter backgrounds, while effectively preserving the echoes of moving vehicles, pedestrians, and other targets, ultimately obtaining clear target traces through detection.

[0066] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A clutter interference suppression method based on subbanding processing, characterized in that: Includes the following steps: S1: Receives monitoring signals containing target reflected echoes, direct waves and clutter, as well as a relatively clean direct wave reference signal; S2: Convert the monitoring signal and the reference signal from the time domain to the frequency domain respectively; S3: Divide the converted frequency domain monitoring signal and frequency domain reference signal into multiple sub-bands evenly; S4: Within each sub-band, based on the sub-band reference signal, clutter suppression processing is performed on the sub-band monitoring signal to remove clutter components related to the reference signal and retain the moving target signal; S5: Combine all sub-band processed signals in frequency band order to obtain the full-band clutter suppressed monitoring signal; S6: Perform coherent processing on the synthesized monitoring signal and the reference signal to achieve target detection and parameter estimation.

2. The clutter interference suppression method based on subbanding processing according to claim 1, characterized in that, In step S4, the clutter suppression processing within each sub-band specifically includes: S41: Construct clutter subspace based on the reference signal of the current subband; S42: Estimate the projection weights of the sub-band monitoring signal onto the clutter subspace; S43: Subtract the clutter estimation component, which is composed of the reference signal and the projection weight, from the sub-band monitoring signal.

3. The clutter interference suppression method based on subbanding processing according to claim 2, characterized in that, The clutter subspace is composed of the reference signal spectrum vector of the current subband.

4. The clutter interference suppression method based on subbanding processing according to claim 1, characterized in that, In step S3, the number and width of sub-bands are dynamically adjusted based on the total bandwidth of the original signal, the system distance resolution requirements, or the intensity of environmental clutter.

5. The clutter interference suppression method based on subbanding processing according to claim 1, characterized in that, Before performing step S4, the amplitude and phase of the sub-band reference signal are calibrated to match the channel characteristics of the sub-band monitoring signal.

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