Urban complex environment clutter suppression method for communication and inductance integrated system

Abstract

The invention relates to an urban complex environment clutter suppression method for a communication and inductance integrated system. The method comprises the following steps: acquiring multi-frame echo data; sequentially performing distance dimension pulse compression and Doppler dimension coherent accumulation on each frame of echo data to obtain a distance-Doppler frequency spectrum of each frame of echo data; and carrying out band coefficient subtraction on the distance-Doppler frequency spectrum of every two adjacent frames of echo data by using the clutter distribution similarity of the two adjacent frames of echo data to obtain the distance-Doppler frequency spectrum after clutter suppression, the coefficient being the ratio of the zero frequency data of every two adjacent frames of echo data. According to the urban complex environment clutter suppression method for the communication and inductance integrated system, the application of a base station to detect a low, slow and small target in the urban complex environment is met, strong clutter suppression is achieved for zero frequency and nearby Doppler channels, the problem of clutter spectrum diffusion can be solved, the slow moving target detection performance is improved, the signal-clutter-noise ratio is increased, and the method is suitable for large-scale popularization and application. The method is suitable for signals with different bandwidths and transmitting powers.

Description

Technical Field

[0001] The present invention belongs to the technical field of wave processing, and particularly relates to a method for suppressing clutter in complex urban environments for a communication-sensing integrated system. Background Art

[0002] As communication devices continue to develop towards higher frequency bands and larger bandwidths, radar and communication systems are becoming increasingly similar in structure, both including components such as transceiver systems, mixers, and filters. This trend has given communication and radar systems more commonalities, leading to the concept of communication-radar integration (communication-sensing integration). By using communication infrastructure such as base stations in the radar system, equipment costs can be reduced, equipment volume can be minimized, and large-scale deployment of radar systems can be achieved; at the same time, equipment utilization rate is improved, and spectrum utilization rate is also enhanced.

[0003] With the continuous increase of future communication signal bandwidths and frequencies, target detection based on communication base stations will become an important direction for the development of future electronic information technologies. "Low, slow, and small" unmanned aerial vehicles (UAVs) are usually small in size, slow in speed, and low in altitude, making them difficult to be detected by traditional optoelectronic detection means. Radar technology can effectively detect low, slow, and small UAVs by detecting electromagnetic wave signals reflected and scattered by targets, without being affected by factors such as light and weather. However, due to the characteristics of "low, slow, and small" targets, such as small radar cross-section (RCS), low flight altitude, and slow speed, the echo signals are weak and are easily submerged by complex ground clutter (such as building reflections and atmospheric refraction clutter) and noise; at the same time, their Doppler frequencies overlap with the clutter frequency domain, and the performance of traditional detection methods deteriorates sharply.

[0004] Currently, the mainstream clutter suppression methods are mainly the Kalman filter and weighted mean filtering technology. The Kalman filter is based on the amplitude response difference operation of an FFT (Fast Fourier Transform) filter bank, and suppresses strong static clutter through a zero-frequency notch. However, in the complex urban clutter background, clutter is widely distributed in the Doppler domain, and the Kalman filter cannot meet the problem of clutter Doppler domain diffusion. The weighted mean filtering technology suppresses the passband ripple through window function weighting, but for meteorological clutter with a certain Doppler velocity and a relatively large clutter spectrum width, since the center position and width of the notch cannot be adjusted in real time according to the actual clutter spectrum center, the suppression effect is often not ideal. In summary, the existing clutter suppression methods are difficult to meet the high-precision detection requirements of "low, slow, and small" UAVs in urban environments. Summary of the Invention

[0005] In order to solve the above problems existing in the prior art, the present invention provides a method for suppressing clutter in complex urban environments for a communication-sensing integrated system. The technical problems to be solved by the present invention are achieved through the following technical solutions:

[0006] The present invention provides a method for suppressing clutter in complex urban environments for a communication-sensing integrated system, including the following steps:

[0007] Obtain multiple frames of echo data;

[0008] Perform range-dimensional pulse compression and Doppler-dimensional coherent integration on each frame of echo data in sequence to obtain the range-Doppler spectrum of each frame of echo data;

[0009] Utilize the similarity of clutter distribution between two adjacent frames of echo data to perform coefficient-subtraction on the range-Doppler spectra of every two adjacent frames of echo data, obtaining the range-Doppler spectrum after clutter suppression, where the coefficient is the ratio of the zero-frequency data of every two adjacent frames of echo data.

[0010] In an implementable manner, the similarity of clutter distribution between two adjacent frames of echo data includes:

[0011] The similarity of clutter distribution in the same range cell in the range-Doppler spectra of every two adjacent frames of echo data.

[0012] In an implementable manner, performing coefficient-subtraction on the range-Doppler spectra of every two adjacent frames of echo data includes:

[0013] Perform coefficient-subtraction on the absolute values of the amplitudes of the same range cell of every two adjacent frames of echo data, where the coefficient is the cancellation coefficient of the current range cell.

[0014] In an implementable manner, the cancellation coefficient of each range cell is: the ratio of the absolute values of the zero-frequency data of each range cell in two adjacent frames of echo data.

[0015] In an implementable manner, the similarity of clutter distribution between two adjacent frames of echo data includes:

[0016] The similarity of clutter amplitude and phase in different range cells in the range-Doppler spectra of every two adjacent frames of echo data.

[0017] In an implementable manner, performing coefficient-subtraction on the range-Doppler spectra of every two adjacent frames of echo data includes:

[0018] Perform coefficient-subtraction on the absolute value of the amplitude of the strongest clutter range cell of one frame of echo data and the absolute values of the amplitudes of each range cell of the other frame of echo data for every two adjacent frames of echo data, where the coefficient is the cancellation coefficient corresponding to each range cell of the other frame of echo data.

[0019] In an implementable manner, the cancellation coefficient corresponding to a range bin of another frame of echo data is: the ratio of the absolute value of the zero-frequency data of the strongest clutter range bin in one frame of echo data to the absolute value of the zero-frequency data of the current range bin in another frame of echo data.

[0020] In an implementable manner, the range-Doppler spectrum S after clutter suppression ij satisfies the formula:

[0021] S ij = |S i | - ψ ij * |S j |;

[0022] where, |S i | is the absolute value of the range-Doppler spectrum of the i-th frame of echo data, |S j | is the absolute value of the range-Doppler spectrum of the j-th frame of echo data, ψ ij is the cancellation coefficient between the i-th frame and the j-th frame, |S i，0 | is the absolute value of the zero-frequency data of the i-th frame of echo data, |S j，0 | is the absolute value of the zero-frequency data of the j-th frame of echo data, and i and j are two adjacent positive integers.

[0023] In an implementable manner, performing range-dimensional pulse compression and Doppler-dimensional coherent integration on each frame of echo data in sequence, including:

[0024] Decomposing each frame of echo signal into several range bins in the range dimension through matched filtering;

[0025] Performing fast Fourier transform on the pulse data in several range bins of each frame of echo signal.

[0026] In an implementable manner, each frame of echo data includes: target echo data and clutter data reflected by the environment.

[0027] Compared with the prior art, the beneficial effects of the present invention:

[0028] The clutter suppression method for an integrated communication and sensing system in an urban complex environment provided by the present invention utilizes the similarity of clutter distribution between two adjacent frames of echo data. Using the ratio of the zero-frequency data of every two adjacent frames of echo data as a coefficient, perform coefficient-subtraction on the range-Doppler spectra of every two adjacent frames of echo data to remove clutter and obtain the range-Doppler spectrum after clutter suppression. The clutter suppression method provided by the present invention meets the application of detecting "low, slow, and small" targets by a base station in an urban complex environment, can solve the problem of clutter spectrum spreading, improve the detection performance of slow-moving targets, improve the signal-to-clutter ratio, and is applicable to signals with different bandwidths and transmission powers. Description of the Drawings

[0029] Figure 1 is a flowchart of the steps of a method for suppressing clutter in an urban complex environment for a communication-sensing integrated system provided by an embodiment of the present invention;

[0030] Figure 2 is a schematic diagram of a range-Doppler clutter map provided by an embodiment of the present invention. Detailed Embodiments

[0031] The following further describes the present invention in detail with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0032] Embodiment 1

[0033] Please refer to Figure 1 , Figure 1 which is a flowchart of the steps of a method for suppressing clutter in an urban complex environment for a communication-sensing integrated system provided by an embodiment of the present invention.

[0034] A method for suppressing clutter in an urban complex environment for a communication-sensing integrated system provided in this embodiment includes the following steps:

[0035] Step 1: Obtain multiple frames of echo data.

[0036] Specifically, the communication-sensing integrated system realizes the cooperative work of communication and radar functions through sharing hardware resources and signal processing algorithms. The receiving end of the communication-sensing integrated system synchronously captures communication signals and radar echoes, and separates the communication signals and radar echoes through separation technology. The multiple frames of echo data in this embodiment are multiple consecutive radar echo signals obtained after separation. In this embodiment, each frame of echo data includes: target echo data and clutter data reflected by the environment.

[0037] Step 2: Perform range-dimensional pulse compression and Doppler-dimensional coherent integration on each frame of echo data in sequence to obtain the range-Doppler spectrum of each frame of echo data.

[0038] In this embodiment, Step 2 includes:

[0039] Decompose each frame of echo signal into several range cells in the range dimension through matched filtering.

[0040] Perform fast Fourier transform on the pulse data in several range cells of each frame of echo signal to generate a Doppler frequency axis, and obtain the range-Doppler spectrum of each frame of echo data.

[0041] Please refer to Figure 2 , Figure 2It is a schematic diagram of the range-Doppler clutter map provided by an embodiment of the present invention. In this embodiment, a clutter map method based on range-Doppler is adopted to detect tangential low-speed targets. The radar echo data is processed by two-dimensional Fourier transform to obtain a range-Doppler spectrum matrix, and then a range-Doppler clutter map is obtained. Based on the range-Doppler clutter map, the radial distance information of the target can be obtained in the range dimension (horizontal axis), and the velocity information of the target can be obtained in the velocity dimension (vertical axis). When detecting tangential low-speed targets, the velocity change of the target can be directly observed through the velocity dimension unit. Figure 2 In Figure 2 , the range size of each clutter unit is ΔR, and the velocity size is ΔV. The range resolution unit is Δr, and the velocity resolution unit is Δv. A clutter unit includes M range resolution units and N velocity resolution units, then ΔR = MΔr and ΔV = NΔv. When M = 1 and N = 1, each clutter detection unit only contains 1 range resolution unit and 1 velocity resolution unit. In this case, the clutter map has the highest fineness, but requires more storage space and longer processing time. Assume Y l (i,j) is the clutter map at coordinates (i,j) during the l-th circle scan. The update formula for the clutter map Y l+1 (i,j) in the (l + 1)-th circle is:

[0042] Y l+1 (i,j) = (1 - w)Y l (i,j) + wX(i,j);

[0043] where w is the weight,

[0044] After iterative updating of the clutter map with multiple scan data, a stable clutter map can be obtained. During the detection process of "low, slow, and small" targets, the clutter is mainly composed of clutter data formed by buildings, roads, bridges, vegetation, lakes, etc. in the urban strong clutter environment, that is, fixed clutter. In the urban strong clutter environment, the clutter amplitude and phase fluctuate greatly at close range; the clutter amplitude and phase fluctuate less at far range. The main reason is the vegetation swing in the close-range unit and the local oscillator phase noise in the bistatic receiving and transmitting system. The fluctuations of both amplitude and phase will cause the clutter energy to spread from zero Doppler frequency to the entire clutter spectrum; when the vegetation echo dominates, the clutter amplitude and phase fluctuate greatly in the slow time domain of the close-range unit; while when the building echo dominates in the far-range unit, the clutter is relatively stable.

[0045] Step 3: Utilize the similarity of the clutter distribution between two adjacent frames of echo data to perform coefficient subtraction on the range-Doppler spectra of every two adjacent frames of echo data to obtain the range-Doppler spectrum after clutter suppression, where the coefficient is the ratio of the zero-frequency data of every two adjacent frames of echo data.

[0046] Specifically, the clutter map cancellation process suppresses clutter by subtracting the clutter map stored value from the echo signal value. After the cancellation process, fixed clutter can be subtracted, improving the target signal-to-clutter ratio. Traditional inter-pulse cancellation processing causes significant energy attenuation to slow targets while suppressing clutter. In this embodiment, to detect "low, slow, and small" targets, using the similarity of clutter distribution between two adjacent frames of echo data, inter-frame cancellation is performed, that is, the clutter range-Doppler spectra of adjacent coherent processing periods are cancelled (the time interval between adjacent processing periods is relatively long, and the target distance, phase, and amplitude change significantly, resulting in less energy loss after cancellation). In this embodiment, a clutter suppression algorithm is studied for typical urban scenarios (such as buildings and trees), the amplitude and phase characteristics of clutter are analyzed, the problem of clutter spectrum energy diffusion is considered, and an inter-frame cancellation clutter suppression algorithm is proposed. Using the similarity of clutter distribution to solve the problem of clutter spectrum diffusion, suppressing clutter near zero frequency and amplitude-phase stable clutter, and solving the problem of non-zero frequency clutter diffusion. It can improve the detection performance of slow-moving targets and the signal-to-clutter ratio. Further, the similarity of clutter distribution is the consistency of clutter amplitude in the time domain, that is, in two adjacent frames of data, the clutter amplitude of the same range cell is the same; in two adjacent frames of data, the strongest clutter cell is fixed in one range cell.

[0047] In this embodiment, the range-Doppler spectrum S after clutter suppression ij satisfies the formula:

[0048] S ij =|S i |-ψ ij *|S j |;

[0049] where, |S i | is the absolute value of the range-Doppler spectrum of the i-th frame of echo data, |S j | is the absolute value of the range-Doppler spectrum of the j-th frame of echo data, ψ ij is the cancellation coefficient between the i-th frame and the j-th frame, |S i，0 | is the absolute value of the zero-frequency data of the i-th frame of echo data, |S j，0 | is the absolute value of the zero-frequency data of the j-th frame of echo data, and i and j are two adjacent positive integers.

[0050] In an implementable manner, by utilizing the similarity of the clutter distribution in the same range bin of the range-Doppler spectra of every two adjacent frames of echo data, clutter map cancellation processing is performed. At this time, the absolute values of the amplitudes of the same range bin of every two adjacent frames of echo data are subtracted with a coefficient, and the coefficient is the cancellation coefficient of the current range bin. The cancellation coefficient of each range bin is: the ratio of the absolute value of the zero-frequency data of each range bin in two adjacent frames of echo data. It should be understood that the zero-frequency data of a range bin is the amplitude of that range bin when the Doppler frequency is zero.

[0051] Exemplarily, when performing clutter map cancellation processing (subtraction with a coefficient) by utilizing the similarity of the clutter distribution in the same range bin of the range-Doppler spectra of every two adjacent frames of echo data, the amplitude S of range bin A in the range-Doppler spectrum S after clutter suppression ij satisfies the formula: ij，A S

[0052] S ij，A = |S i，A | - ψ ij，A * |S j，A |;

[0053] where, |S i，A | is the absolute value of the amplitude of range bin A in the i-th frame of echo data, |S j，A | is the absolute value of the amplitude of range bin A in the j-th frame of echo data, ψ ij，A is the cancellation coefficient of range bin A for the i-th and j-th frames, |S i，A0 | is the absolute value of the zero-frequency data of range bin A in the i-th frame of echo data, |S j，A0 | is the absolute value of the zero-frequency data of range bin A in the j-th frame of echo data, i and j are two adjacent positive integers, and A is a positive integer.

[0054] Cancellation is performed for each range bin in two adjacent frames of echo data, and then data after clutter suppression for one frame can be obtained. After performing cancellation for every two adjacent frames among the received X frames of echo data, X - 1 frames of data after clutter suppression can be obtained. Optionally, if i > j or i < j, the range-Doppler spectrum of the latter frame of echo data can be subtracted from the range-Doppler spectrum of the former frame of echo data, or the range-Doppler spectrum of the former frame of echo data can be subtracted from the range-Doppler spectrum of the latter frame of echo data.

[0055] In an implementable manner, clutter map cancellation processing is performed by utilizing the similarity of the clutter amplitude and phase of different range cells in the range-Doppler spectrum of every two adjacent frames of echo data. At this time, the absolute value of the amplitude of the strongest clutter range cell in one frame of echo data among every two adjacent frames of echo data and the absolute values of the amplitudes of the remaining range cells in the other frame of echo data are subtracted with coefficients respectively, and the coefficient is the cancellation coefficient corresponding to the remaining range cells in the other frame of echo data. The cancellation coefficient corresponding to a range cell in the other frame of echo data is: the ratio of the absolute value of the zero-frequency data of the strongest clutter range cell in one frame of echo data to the absolute value of the zero-frequency data of the current range cell in the other frame of echo data.

[0056] Exemplarily, by utilizing the similarity of the clutter amplitude and phase of different range cells in the range-Doppler spectrum of every two adjacent frames of echo data, that is, the strongest clutter cell is fixedly located in one range cell, when performing clutter map cancellation processing (subtraction with coefficients), the amplitude S of range cell B in the range-Doppler spectrum S after clutter suppression ij satisfies the formula: ij，B S

[0057] S ij，B = |S i，Max |- ψ ij，B * |S j，B |;

[0058] where, |S i，Max | is the absolute value of the amplitude of the range cell Max with the largest clutter amplitude in the i-th frame of echo data, |S j，B | is the absolute value of the amplitude of range cell B in the j-th frame of echo data, ψ ij，B is the cancellation coefficient of range cell B between the i-th frame and the j-th frame, |S i，Max0 | is the absolute value of the zero-frequency data of the range cell Max with the largest clutter amplitude in the i-th frame of echo data, |S j，B0 | is the absolute value of the zero-frequency data of range cell B in the j-th frame of echo data, i and j are two adjacent positive integers, and B is a positive integer.

[0059] This embodiment provides a clutter suppression method for urban complex environment in a communication-sensing integrated system. By utilizing the similarity of clutter distribution in adjacent two-frame echo data, taking the ratio of zero-frequency data of every two adjacent-frame echo data as a coefficient, subtracting the range-Doppler spectrum of every two adjacent-frame echo data with the coefficient to remove clutter, and obtaining the range-Doppler spectrum after clutter suppression. The clutter suppression method provided by this embodiment meets the application of detecting "low, slow and small" targets by base stations in urban complex environments, is applicable to detecting "low, slow and small" UAV targets through signals transmitted by existing communication base stations, can solve the problem of clutter spectrum spreading, achieve strong clutter suppression for zero-frequency and nearby Doppler channels, improve the detection performance of slow-moving targets, and improve the signal-to-clutter ratio. The clutter suppression method for urban complex environment provided by this embodiment is applicable to signals with different bandwidths and transmission powers, meets the application in complex scenarios, can enhance the effect and resolution of target detection, and improve the detection performance.

[0060] The above content is a further detailed description of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention belongs, without departing from the concept of the present invention, several simple deductions or substitutions can be made, and all should be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for suppressing clutter in complex urban environments for a synaesthesia integrated system, characterized in that: The following steps are involved: Acquire multiple frames of echo data; Performing range-dimensional pulse compression and Doppler-dimensional coherent accumulation on each frame of echo data in turn to obtain a range-Doppler spectrum of each frame of echo data; By using the similarity of clutter distribution between two adjacent frames of echo data, the range-Doppler spectrum of each two adjacent frames of echo data is subtracted with coefficients to obtain the range-Doppler spectrum after clutter suppression, wherein the coefficient is the ratio of the zero-frequency data of each two adjacent frames of echo data.

2. The method for suppressing clutter in complex urban environments for the synaesthesia integrated system according to claim 1 is characterized in that: The similarity of clutter distribution between two adjacent frames of echo data includes: The similarity of clutter distribution in the same range unit in the range-Doppler spectrum of each two adjacent frames of echo data.

3. The method for suppressing clutter in complex urban environments for the synaesthesia integrated system according to claim 2 is characterized in that: The range-Doppler spectrum of each two adjacent frames of echo data is subtracted with coefficients, including: The absolute values ​​of the amplitudes of the same distance unit of each two adjacent frames of echo data are subtracted with coefficients, and the coefficients are the cancellation coefficients of the current distance unit.

4. The method for suppressing clutter in complex urban environments for the synaesthesia integrated system according to claim 3 is characterized in that: The cancellation coefficient of each distance unit is: the ratio of the absolute values ​​of the zero-frequency data of each distance unit in two adjacent frames of echo data.

5. The method for suppressing clutter in complex urban environments for the synaesthesia integrated system according to claim 1, characterized in that: The similarity of clutter distribution between two adjacent frames of echo data includes: The similarity of the amplitude and phase of clutter in different range units in the range-Doppler spectrum of each adjacent two frames of echo data.

6. The method for suppressing clutter in complex urban environments for the synaesthesia integrated system according to claim 5, characterized in that: The range-Doppler spectrum of each two adjacent frames of echo data is subtracted with coefficients, including: The absolute value of the amplitude of the strongest clutter distance unit of one frame of echo data in each of two adjacent frames of echo data and the absolute value of the amplitude of each distance unit of the other frame of echo data are subtracted with coefficients, and the coefficients are cancellation coefficients corresponding to each distance unit of the other frame of echo data.

7. The method for suppressing clutter in complex urban environments for the synaesthesia integrated system according to claim 6, characterized in that: The cancellation coefficient corresponding to a distance unit of another frame of echo data is: the ratio of the absolute value of the zero-frequency data of the strongest clutter distance unit in one frame of echo data to the absolute value of the zero-frequency data of the current distance unit in another frame of echo data.

8. The method for suppressing clutter in complex urban environments for the synaesthesia integrated system according to claim 1 is characterized in that: Range-Doppler spectrum S after clutter suppression ij Satisfy the formula: S ij =|S i |-ψ ij *|S j |; Among them, |S i | is the absolute value of the range-Doppler spectrum of the i-th frame echo data, |S j | is the absolute value of the distance-Doppler spectrum of the j-th frame echo data, ψ ij is the cancellation coefficient between the i-th frame and the j-th frame, |S i，0 | is the absolute value of the zero-frequency data of the i-th frame echo data, |S j，0 | is the absolute value of the zero-frequency data of the j-th frame echo data, and i and j are two adjacent positive integers.

9. The method for suppressing clutter in complex urban environments for the synaesthesia integrated system according to claim 1, characterized in that: Each frame of echo data is subjected to range-dimensional pulse compression and Doppler-dimensional coherent accumulation in turn, including: Each frame of echo signal is decomposed into several distance units in the distance dimension through matched filtering; The pulse data in several range units of each frame of echo signal are subjected to fast Fourier transform.

10. The method for suppressing clutter in complex urban environments for the synaesthesia integrated system according to claim 1, characterized in that: Each frame of echo data includes target echo data and clutter data reflected by the environment.

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