A channel equalization method based on inter-channel amplitude and phase error distribution characteristics

Abstract

The application discloses a channel equalization method based on inter-channel amplitude and phase error distribution characteristics, and comprises the following steps: performing distance direction pulse compression and azimuth direction weighted Fourier transform on original echo data of two channels respectively to obtain Doppler domain data; taking a first channel as a reference channel, calculating amplitude ratio values of the two channels, extracting amplitude error compensation factors by using a sliding window median filter, and compensating the second channel by using the amplitude error compensation factors; performing interference processing on the distance Doppler domain data of the two channels after amplitude compensation to obtain an interference phase difference between the two channels, constructing a cost function according to the interference phase difference, averaging the interference phase along the distance direction, calculating the cost function value by traversing each Doppler unit, making the cost function value converge to a minimum through progressive iteration, and recording the compensation phase difference corresponding to each Doppler unit at this time; performing sliding average processing on the compensation phase difference obtained through iteration to obtain a phase error weight vector, compensating the second channel by using the phase error weight vector, completing phase equalization, realizing channel equalization, performing offset phase center antenna processing on the distance Doppler domain data of the two channels after channel equalization to obtain a clutter suppressed distance Doppler map, and improving the system clutter suppression capability.

Description

Technical Field

[0001] This invention relates to the field of radar technology, and in particular to a channel equalization method based on the distribution characteristics of amplitude and phase errors between channels. Background Technology

[0002] In wide-area GMTI mode, ground clutter severely impacts radar detection performance when airborne radar systems detect the ground. Furthermore, ground clutter from different directions exhibits varying radial velocities relative to the radar platform, increasing its spectral width in the Doppler domain and complicating the detection of slow-moving targets. Therefore, clutter suppression becomes a crucial step in signal processing within the wide-area GMTI mode. While traditional space-time adaptive processing techniques effectively suppress mainlobe clutter, they are only suitable for multi-channel systems, resulting in high system costs, complex algorithms, and heavy computational demands, making real-time implementation impractical for engineering applications.

[0003] Offset phase center antenna technology is suitable for dual-channel systems due to its simple algorithm, low computational load, and ease of real-time implementation. However, for airborne radar systems, the unavoidable influence of non-ideal factors such as aircraft motion errors and channel imbalances leads to amplitude and phase errors between channels, thus affecting clutter suppression performance. Therefore, for airborne radar systems, equalizing the amplitude and phase errors between channels before clutter suppression is crucial to improve clutter suppression performance. Traditional adaptive methods based on smoothing filters apply a moving weighted smoothing of amplitude and phase errors using a certain two-dimensional window in both the range-Doppler and range-frequency Doppler domains. However, due to abrupt changes in amplitude and phase errors at the junction of the main lobe edge and side lobes, the estimation accuracy of amplitude and phase errors in this region is poor, resulting in a large amount of residual clutter. Furthermore, the use of sliding window smoothing leads to a significant loss in the signal-to-noise ratio of the target signal. Summary of the Invention

[0004] Purpose of the invention: The purpose of this invention is to provide a channel equalization method based on the distribution characteristics of amplitude and phase errors between channels, thereby solving the problems in the background art.

[0005] Technical Solution: To achieve the above objectives, the present invention provides the following technical solution:

[0006] The channel equalization method based on the distribution characteristics of amplitude and phase errors between channels, as described in this invention, includes the following steps:

[0007] Step 1: Perform range pulse compression and azimuth weighted Fourier transform on the raw echo data of the two channels respectively to obtain the range Doppler domain data of each channel;

[0008] Step 2: Using the first channel as the reference channel, calculate the amplitude ratio of the two channels, extract the amplitude error compensation factor from the amplitude ratio using sliding window median filtering, and use the amplitude error compensation factor to perform amplitude compensation on the second channel;

[0009] Step 3: Perform interferometric processing on the two-channel range Doppler domain data after amplitude compensation to obtain the interferometric phase difference between the two channels. Construct a cost function based on the interferometric phase difference, average the interferometric phase along the range direction, calculate the cost function value by traversing each Doppler cell, and converge the cost function value to the minimum through progressive iteration. Record the compensation phase difference corresponding to each Doppler cell at this time.

[0010] Step 4: Perform a moving average process on the compensated phase difference obtained from the iteration to obtain the phase error weight vector. Compensate the phase error weight vector to the second channel to complete phase equalization and achieve channel equalization.

[0011] Step 5: Perform offset phase center antenna processing on the range Doppler domain data of the two channels after channel equalization to obtain the range Doppler map after clutter suppression.

[0012] Further, step 2 is as follows: calculate the ratio of the amplitudes of the two channel range-Doppler domain data; perform two-dimensional sliding window median filtering on the amplitude ratio, and use the filtering result as the amplitude error compensation factor; multiply the amplitude error compensation factor with the range-Doppler domain data of the second channel to obtain the amplitude-equalized second channel data.

[0013] Further, step 3 is as follows: perform conjugate multiplication on the two-channel range-Doppler domain data after amplitude equalization to extract the interference phase difference; construct a cost function with the compensation phase difference as the variable based on the interference phase difference; average the interference phase along the range direction, and calculate the cost function value under the current compensation phase difference for each Doppler cell; update the compensation phase difference of each Doppler cell successively along the direction that reduces the cost function, and perform progressive iteration until the cost function value reaches the minimum or the phase error variance meets the preset threshold, and take the compensation phase difference at this time as the phase error of the Doppler cell.

[0014] Further, step 4 is as follows: the phase error of each Doppler unit obtained by the iteration is smoothed using a two-dimensional moving average window to eliminate random disturbances and generate a phase error weight vector; the phase error weight vector is compensated to the second channel, and the data of the second channel is multiplied by the complex exponential form of the phase error weight vector to complete the phase equalization.

[0015] Further, step 5 is as follows: Calculate the variance of amplitude error and the variance of phase error of the two channels before channel equalization; calculate the variance of amplitude error and the variance of phase error of the two channels after channel equalization; use the ratio of amplitude error variance before equalization to amplitude error variance after equalization as the amplitude error improvement factor, and use the ratio of phase error variance before equalization to phase error variance after equalization as the phase error improvement factor. The larger the improvement factor value, the better the channel equalization performance.

[0016] The channel equalization system based on the distribution characteristics of amplitude and phase errors between channels, as described in this invention, includes:

[0017] Transformation module: used to perform range pulse compression and azimuth weighted Fourier transform on the raw echo data of the two channels respectively to obtain range Doppler domain data of each channel;

[0018] Compensation module: Used with the first channel as a reference channel, calculate the amplitude ratio of the two channels, extract the amplitude error compensation factor from the amplitude ratio using sliding window median filtering, and use the amplitude error compensation factor to perform amplitude compensation on the second channel;

[0019] Phase difference module: Used to perform interferometric processing on the two-channel range Doppler domain data after amplitude compensation, obtain the interferometric phase difference between the two channels, construct a cost function based on the interferometric phase difference, average the interferometric phase along the range direction, calculate the cost function value by traversing each Doppler cell, and converge the cost function value to the minimum through progressive iteration, and record the compensation phase difference corresponding to each Doppler cell at this time.

[0020] Equalization module: Used to perform moving average processing on the compensated phase difference obtained by iteration, obtain the phase error weight vector, compensate the phase error weight vector to the second channel, complete the phase equalization, and realize channel equalization;

[0021] Processing module: Used to perform offset phase center antenna processing on the range Doppler domain data of the two channels after channel equalization to obtain the range Doppler map after clutter suppression.

[0022] Furthermore, in the compensation module, the specific steps are as follows: calculate the ratio of the amplitudes of the two channels' distance-Doppler domain data; perform two-dimensional sliding window median filtering on the amplitude ratio, and use the filtering result as the amplitude error compensation factor; multiply the amplitude error compensation factor by the distance-Doppler domain data of the second channel to obtain the amplitude-equalized second channel data.

[0023] Furthermore, in the phase difference module, the specific steps are as follows: The two-channel range-Doppler domain data after amplitude equalization are multiplied by conjugate to extract the interference phase difference; a cost function with the compensation phase difference as the variable is constructed based on the interference phase difference; the interference phase is averaged along the range direction, and the cost function value under the current compensation phase difference is calculated for each Doppler cell; the compensation phase difference of each Doppler cell is updated successively along the direction that reduces the cost function, and progressive iteration is performed until the cost function value reaches the minimum or the phase error variance meets the preset threshold. The compensation phase difference at this time is then used as the phase error of that Doppler cell.

[0024] Furthermore, in the equalization module, the phase error of each Doppler unit obtained by iteration is smoothed using a two-dimensional moving average window to eliminate random disturbances and generate a phase error weight vector; the phase error weight vector is compensated to the second channel, and the data of the second channel is multiplied by the complex exponential form of the phase error weight vector to complete the phase equalization.

[0025] Furthermore, the processing module specifically performs the following: Calculate the variances of amplitude and phase errors of the two channels before channel equalization; calculate the variances of amplitude and phase errors of the two channels after channel equalization; use the ratio of the amplitude error variance before equalization to the amplitude error variance after equalization as the amplitude error improvement factor, and use the ratio of the phase error variance before equalization to the phase error variance after equalization as the phase error improvement factor. A larger improvement factor value indicates better channel equalization performance.

[0026] Beneficial Effects: Compared with existing technologies, this invention has the following significant advantages: The channel equalization method of this invention addresses the clutter residue problem caused by abrupt amplitude and phase error changes at the main lobe clutter edge in traditional smoothing filtering-based channel equalization methods, which utilize the characteristics of two-dimensional uniform distribution and distance-oriented uniform distribution of inter-channel amplitude and phase errors, respectively. This significantly improves the clutter suppression capability of the system. While achieving inter-channel amplitude and phase error equalization and improving the system's clutter suppression capability, the channel equalization method of this invention effectively reduces the signal-to-noise ratio loss of the target signal, further facilitating subsequent target detection. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0028] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] Furthermore, in the description of the embodiments of this application, the terms "first," "second," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. The terms "comprising" and "having," and any variations thereof, as used in this application, are intended to cover non-exclusive inclusion.

[0030] This invention provides a channel equalization method based on the distribution characteristics of amplitude and phase errors between channels, comprising the following steps:

[0031] Step 1: In wide-area GMTI mode, range pulse compression and azimuth weighted FFT are performed on the raw echo data of the two channels to obtain range Doppler domain data, i.e., DBS image.

[0032] Step 2: Using channel 1 as the reference channel, calculate the amplitude ratio of the two channels, obtain the amplitude error compensation factor using sliding window median filtering, and compensate for it in channel 2 to complete the amplitude compensation; Step 2.1: Based on the obtained distance-Doppler domain data of the two channels, calculate the amplitude of the distance-Doppler domain data of the two channels, and obtain the ratio of the amplitudes of the two channel data, expressed as:

[0033]

[0034] in, and These are the distance-Doppler domain data for channel 1 and channel 2, respectively.

[0035] Step 2.2: Perform median filtering on the amplitude ratio of the obtained two-channel data. The sliding median filtering process is as follows:

[0036]

[0037] in, Indicates the distance to the window radius. Indicates the radius of the Doppler window. Represents a two-dimensional window matrix. This indicates that the matrix is ​​being taken as a median. This is the unit amplitude error compensation factor.

[0038] Step 2.3: Apply the amplitude error compensation factor to channel 2 to complete amplitude equalization. The data for channel 2 after amplitude equalization is as follows:

[0039]

[0040] in, This is the distance Doppler domain data for channel 2 after amplitude equalization.

[0041] Step 3: Interfere the two-channel range-Doppler domain data, construct a cost function based on the phase difference between the two channels, average the interference phase along the range direction, traverse each Doppler cell and calculate the cost function value, obtain the minimum cost function value (which can be equivalent to the variance of the phase difference between the two channels satisfying a certain threshold), and record the corresponding phase difference.

[0042] Step 3.1: Perform interferometric processing on the two-channel distance-Doppler data after amplitude equalization to obtain the interferometric phase difference:

[0043]

[0044] in, This represents the phase difference between the two channels.

[0045] Step 3.2: Construct a cost function based on the phase difference between the two channels. Average the interference phase along the range direction, traverse each Doppler cell and calculate the cost function value. Use an iterative method to obtain the minimum cost function value (which can be equivalent to the variance of the phase difference between the two channels satisfying a certain threshold). The iterative process is as follows:

[0046]

[0047] in, For the number of iterations, , Indicates the first The second iteration The expression for the compensated phase difference on each Doppler unit is:

[0048]

[0049] in, The number of Doppler units, This represents the number of distance units.

[0050] Step 4: Perform a moving average process on the iterated phase error to obtain the phase error weight vector, and then compensate the phase error weight vector into channel 2 to complete the channel equalization.

[0051] Step 4.1: Based on the phase error obtained after completing the iteration of claim 3, perform a moving average process on it to obtain the phase error weight vector:

[0052]

[0053] in, Weighted radius for distance window Weighted radius of the Doppler window.

[0054] Step 4.2: Compensate the phase error weight vector into channel 2 to complete phase equalization.

[0055]

[0056] in, Range Doppler domain data for channel 2 after phase equalization

[0057] Step 5: Perform DPCA on the range Doppler data of the two channels after channel equalization to obtain the clutter-suppressed range Doppler image. Details are as follows:

[0058] The mean and variance of the amplitude and phase of the two channels before and after channel equalization can reflect the channel equalization effect. As an evaluation index of channel equalization performance, the amplitude and phase error factor before channel equalization is used. Amplitude and phase error factors after channel equalization Amplitude error improvement factor and phase error improvement factor Specifically:

[0059] Channel equalization front amplitude phase error factor Defined as the ratio of the system responses of the two channels before channel equalization, its expression is:

[0060]

[0061] in, For the system function of channel 1, This is the system function for channel 2. In reality, we don't obtain the system's true response function; instead, we obtain the output functions of channels 1 and 2. and Given the same input signals, we approximate the ratio of the system functions to the ratio of the output functions of the two channels. The amplitude error before channel equalization has a mean and variance of [missing information]. and . The phase error before channel equalization has a mean and variance of [missing information]. and .

[0062] Amplitude and phase error factor after channel equalization Defined as the ratio of the responses of the two channels after channel equalization, the expression is:

[0063]

[0064] in, This is the system function for channel 2 after channel equalization. This is the output function of channel 2 after channel equalization. The amplitude error after channel equalization has a mean and variance of [missing information]. and . The phase error after channel equalization has a mean and variance of [missing information]. and .

[0065] Dual-channel amplitude error improvement factor and phase error improvement factor Defined as the ratio of the variances of the amplitude and phase errors before and after channel equalization, its expression is:

[0066]

[0067] Improvement Factors and The larger the value, the smaller the amplitude and phase error after channel equalization, and the better the channel equalization performance.

Claims

1. A channel equalization method based on the distribution characteristics of amplitude and phase errors between channels, characterized in that, Includes the following steps: Step 1: Perform range pulse compression and azimuth weighted Fourier transform on the raw echo data of the two channels respectively to obtain the range Doppler domain data of each channel; Step 2: Using the first channel as the reference channel, calculate the amplitude ratio of the two channels, extract the amplitude error compensation factor from the amplitude ratio using sliding window median filtering, and use the amplitude error compensation factor to perform amplitude compensation on the second channel; Step 3: Perform interferometric processing on the two-channel range Doppler domain data after amplitude compensation to obtain the interferometric phase difference between the two channels. Construct a cost function based on the interferometric phase difference, average the interferometric phase along the range direction, calculate the cost function value by traversing each Doppler cell, and converge the cost function value to the minimum through progressive iteration. Record the compensation phase difference corresponding to each Doppler cell at this time. Step 4: Perform a moving average process on the compensated phase difference obtained from the iteration to obtain the phase error weight vector. Compensate the phase error weight vector to the second channel to complete the phase equalization and achieve channel equalization. Step 5: Perform offset phase center antenna processing on the range Doppler domain data of the two channels after channel equalization to obtain the range Doppler map after clutter suppression.

2. The channel equalization method based on the distribution characteristics of amplitude and phase errors between channels according to claim 1, characterized in that, Step 2 is as follows: Calculate the ratio of the amplitudes of the two-channel distance-Doppler domain data; perform two-dimensional sliding window median filtering on the amplitude ratio, and use the filtering result as the amplitude error compensation factor; multiply the amplitude error compensation factor with the distance-Doppler domain data of the second channel to obtain the amplitude-equalized second channel data.

3. The channel equalization method based on the distribution characteristics of amplitude and phase errors between channels according to claim 1, characterized in that, Step 3 is as follows: Perform conjugate multiplication on the two-channel range-Doppler domain data after amplitude equalization to extract the interference phase difference; construct a cost function with the compensation phase difference as the variable based on the interference phase difference; average the interference phase along the range direction, and calculate the cost function value under the current compensation phase difference for each Doppler cell; update the compensation phase difference of each Doppler cell successively along the direction that reduces the cost function, and perform progressive iteration until the cost function value reaches the minimum or the phase error variance meets the preset threshold, and take the compensation phase difference at this time as the phase error of the Doppler cell.

4. The channel equalization method based on the distribution characteristics of amplitude and phase errors between channels according to claim 1, characterized in that, Step 4 is as follows: The phase error of each Doppler unit obtained by the iteration is smoothed by using a two-dimensional moving average window to eliminate random disturbances and generate a phase error weight vector; the phase error weight vector is compensated to the second channel, and the data of the second channel is multiplied by the complex exponential form of the phase error weight vector to complete the phase equalization.

5. The channel equalization method based on the distribution characteristics of amplitude and phase errors between channels according to claim 1, characterized in that, Step 5 is as follows: Calculate the variance of amplitude error and the variance of phase error of the two channels before channel equalization; calculate the variance of amplitude error and the variance of phase error of the two channels after channel equalization; use the ratio of amplitude error variance before equalization to amplitude error variance after equalization as the amplitude error improvement factor, and use the ratio of phase error variance before equalization to phase error variance after equalization as the phase error improvement factor. The larger the improvement factor value, the better the channel equalization performance.

6. A channel equalization system based on the distribution characteristics of amplitude and phase errors between channels, characterized in that, include: Transformation module: used to perform range pulse compression and azimuth weighted Fourier transform on the raw echo data of the two channels respectively to obtain range Doppler domain data of each channel; Compensation module: Used with the first channel as a reference channel, calculate the amplitude ratio of the two channels, extract the amplitude error compensation factor from the amplitude ratio using sliding window median filtering, and use the amplitude error compensation factor to perform amplitude compensation on the second channel; Phase difference module: Used to perform interferometric processing on the two-channel range Doppler domain data after amplitude compensation, obtain the interferometric phase difference between the two channels, construct a cost function based on the interferometric phase difference, average the interferometric phase along the range direction, calculate the cost function value by traversing each Doppler cell, and converge the cost function value to the minimum through progressive iteration, and record the compensation phase difference corresponding to each Doppler cell at this time. Equalization module: Used to perform moving average processing on the compensated phase difference obtained by iteration, obtain the phase error weight vector, compensate the phase error weight vector to the second channel, complete the phase equalization, and realize channel equalization; Processing module: Used to perform offset phase center antenna processing on the range Doppler domain data of the two channels after channel equalization to obtain the range Doppler map after clutter suppression.

7. A channel equalization system based on the distribution characteristics of amplitude and phase errors between channels according to claim 6, characterized in that, The compensation module works as follows: calculate the ratio of the amplitudes of the two channels' distance-Doppler domain data; perform two-dimensional sliding window median filtering on the amplitude ratio, and use the filtering result as the amplitude error compensation factor; multiply the amplitude error compensation factor by the distance-Doppler domain data of the second channel to obtain the amplitude-equalized data of the second channel.

8. A channel equalization system based on the distribution characteristics of amplitude and phase errors between channels according to claim 6, characterized in that, In the phase difference module, the specific steps are as follows: The two-channel range-Doppler domain data after amplitude equalization are multiplied by conjugate to extract the interference phase difference; a cost function with the compensation phase difference as the variable is constructed based on the interference phase difference; the interference phase is averaged along the range direction, and the cost function value under the current compensation phase difference is calculated for each Doppler cell; the compensation phase difference of each Doppler cell is updated successively along the direction that reduces the cost function, and progressive iteration is performed until the cost function value reaches the minimum or the phase error variance meets the preset threshold. The compensation phase difference at this point is then used as the phase error of that Doppler cell.

9. A channel equalization system based on the distribution characteristics of amplitude and phase errors between channels according to claim 6, characterized in that, In the equalization module, the phase error of each Doppler unit obtained by iteration is smoothed using a two-dimensional moving average window to eliminate random disturbances and generate a phase error weight vector; the phase error weight vector is compensated to the second channel, and the data of the second channel is multiplied by the complex exponential form of the phase error weight vector to complete the phase equalization.

10. A channel equalization system based on the distribution characteristics of amplitude and phase errors between channels according to claim 6, characterized in that, In the processing module, the specific steps are as follows: Calculate the variance of amplitude error and the variance of phase error of the two channels before channel equalization; calculate the variance of amplitude error and the variance of phase error of the two channels after channel equalization; use the ratio of amplitude error variance before equalization to amplitude error variance after equalization as the amplitude error improvement factor, and use the ratio of phase error variance before equalization to phase error variance after equalization as the phase error improvement factor. The larger the improvement factor value, the better the channel equalization performance.

Images