Millimeter wave radar moving target detection method based on scale inverse fourier processing

Abstract

This invention provides a millimeter-wave radar moving target detection method based on scaled inverse Fourier transform processing. The method involves performing a time-reversal transform on the echo signal in the range-frequency-slow-time domain to obtain the echo signal. Then, a scaled Fourier transform is performed on the echo signal in both the frequency and slow-time domains to extract the peak value of the range-time data in the scaled frequency domain, thus obtaining the target's radial velocity *v*. Based on the obtained target radial velocity, a phase compensation function is constructed to compensate for the target's radial velocity. A one-dimensional search is then performed within a set radial acceleration search range to obtain an estimate of the target's radial acceleration. Finally, a coherent cumulative phase compensation function is constructed again using the target's radial velocity and radial acceleration to complete the accumulation of the target's radial and Doppler domains. This method avoids high-dimensional parameter search operations, only requiring a one-dimensional parameter matching search step for the maximum peak value of the radial acceleration, significantly reducing computational complexity.

Description

Technical Field

[0001] This invention belongs to the field of radar monitoring technology, and in particular relates to a method for detecting moving targets in millimeter-wave radar based on scale inverse Fourier processing. Background Technology

[0002] For radar moving target detection, using multiple pulse echo signals to accumulate energy over a long period is an effective focusing technique that can significantly improve the signal-to-noise ratio (SNR) of the moving target echo and increase the radar's detection probability. Long-term accumulation algorithms can be broadly classified into non-coherent accumulation and coherent accumulation methods. Typical non-coherent accumulation methods ignore the phase information of the target echo signal, only utilizing amplitude to accumulate the energy of multiple pulses. The echo envelope is superimposed and accumulated in amplitude, which significantly reduces detection performance in low SNR environments.

[0003] Compared to non-coherent accumulation algorithms, coherent accumulation algorithms utilize not only the amplitude information of the target signal but also the phase information of the echo signal, superimposing the echo signals in phase to achieve a higher signal-to-noise ratio (SNR) gain. Coherent accumulation algorithms use Doppler filter banks to focus the target signal energy, thereby enhancing the target's SNR. However, due to the motion characteristics of high-speed maneuvering targets, two problems may arise during long-term coherent accumulation processing: the phenomenon of crossing range cells and the phenomenon of crossing Doppler cells. Furthermore, the complex Doppler ambiguity phenomena further caused by Doppler ambiguity and Doppler spectrum splitting restrict the application of existing frequency-domain coherent accumulation methods, affecting the final accumulation effect on the target. Therefore, researching accumulation methods for complex Doppler fuzzy moving targets and addressing cross-range cell and cross-Doppler cell phenomena, as well as potential complex Doppler fuzziness issues, during coherent accumulation can effectively enhance the signal-to-noise ratio of targets and is of great significance for improving the weak target detection capability of radar systems. However, existing technologies still face the following challenges in addressing cross-range cell and cross-Doppler cell phenomena, and even potential complex Doppler fuzziness issues, during coherent accumulation:

[0004] (1) During long-term accumulation, due to the motion characteristics of the target, the motion parameters of the target at each order will be coupled with the signal parameters, which can easily cause range migration and Doppler broadening, thus reducing the performance of coherent accumulation.

[0005] (2) Due to the limited pulse repetition frequency parameter of the radar system, fast-moving targets are prone to Doppler ambiguity, and high-speed maneuvering targets are prone to more complex Doppler ambiguity phenomena such as Doppler spectrum splitting.

[0006] (3) In the current research, although the high-dimensional parameter search method guarantees the cumulative performance, the huge computational complexity limits the use of the algorithm. Summary of the Invention

[0007] Purpose of the invention: In order to solve the problems existing in the prior art, the present invention provides a millimeter-wave radar moving target detection method based on scale inverse Fourier processing.

[0008] Technical solution: This invention discloses a millimeter-wave radar moving target detection method based on scale inverse Fourier processing, characterized in that:

[0009] For echo signals in the distance frequency-slow time domain Perform time reversal transformation to obtain the echo signal. ,in Indicates distance frequency, It is a slow-time variable. Functions representing time reversal and conjugate operations;

[0010] right Perform a joint scaling Fourier transform on both frequency and slow time to obtain , To Distance-time obtained by performing an inverse Fourier transform of the scale; To The scale frequency is obtained by performing an inverse Fourier transform on the scale.

[0011] extract The target radial velocity is obtained based on the peak value of distance-time in the scale frequency domain and the peak position. ;

[0012] Based on the obtained target radial velocity, a phase compensation function is constructed to... After compensation, a one-dimensional search is performed within the set radial acceleration search range to obtain the estimated value of the target radial acceleration;

[0013] Relevant information about the target can be extracted by the target's radial velocity; or relevant information about the target can be extracted by the target's radial acceleration. The relevant information includes information other than the target's radial velocity and radial acceleration, such as target detection, trajectory, or position.

[0014] Furthermore, the time reversal transformation involves performing time reversal and conjugation operations on the echo signal, specifically:

[0015] ;

[0016] Where * denotes the conjugate operation. Indicates to Perform a slow time reversal; The expression is:

[0017] ;

[0018] Where B is the bandwidth of the transmitted signal, and c is the speed of electromagnetic wave propagation. For the carrier frequency, Indicates the current slow time The instantaneous slant range between the target and the radar.

[0019] Furthermore, the aforementioned Perform a joint scaling Fourier transform on both frequency and slow-time parameters, specifically: [The text abruptly ends here, likely due to an incomplete sentence or a formatting error.] Perform a scaling Fourier transform along the frequency dimension:

[0020] ;

[0021] Where B is the bandwidth of the transmitted signal, and c is the speed of electromagnetic wave propagation. For carrier frequency;

[0022] Then to Perform a scaling Fourier transform in the slow time dimension:

[0023] ;

[0024] in, Indicates the wavelength of the transmitted signal. It is the Dirac function.

[0025] Furthermore, the target radial velocity is obtained based on the peak position, specifically as follows:

[0026] ;

[0027] Where c is the speed of electromagnetic wave propagation. This represents the location of the peak value over time.

[0028] Furthermore, the estimated value of the target radial acceleration is obtained as follows:

[0029] Set the maximum value of radial acceleration. Set the search range based on the maximum value;

[0030] Set a fixed step size to extract acceleration sampling points within the search range;

[0031] Construct a phase compensation function for each sampling point :

[0032] ;

[0033] in, The acceleration value corresponding to the velocity sampling point. The velocity estimate can be v, where c is the speed of electromagnetic wave propagation. For carrier frequency;

[0034] Based on the phase compensation function Perform phase compensation:

[0035] ;

[0036] in, The echo signal after phase compensation;

[0037] Perform a slow-time Fourier transform and a frequency-time inverse Fourier transform on all phase-compensated echo signals. Select the radial acceleration with the largest energy peak from the echo signals after the inverse Fourier transform as the optimal radial acceleration.

[0038] Furthermore, the search scope was set as follows: .

[0039] Furthermore, extracting relevant target information through radial acceleration specifically involves constructing a coherent cumulative processing function based on the radial acceleration:

[0040] ;

[0041] The echo signal is compensated using a coherent cumulative processing function:

[0042] ;

[0043] in, For the compensated echo signal, The wavelength of the transmitted signal;

[0044] right Perform inverse Fourier transform in the frequency dimension and Fourier transform in the slow time dimension; based on the transformed echo signal, extract other information about the target:

[0045] ;

[0046] in, This is the coherent cumulative processing time for the radar system.

[0047] Furthermore, extracting other information about the target through its radial velocity involves: after obtaining the target's radial velocity, constructing a phase compensation function to compensate the echo signal, and then extracting relevant target information based on the compensated echo signal.

[0048] A computer device includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement the steps of the millimeter-wave radar moving target detection method based on scale inverse Fourier processing.

[0049] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the millimeter-wave radar moving target detection method based on scale inverse Fourier processing.

[0050] Beneficial effects:

[0051] This invention addresses the problems of cross-range cell and Doppler broadening in radar moving targets by utilizing an improved scaled inverse Fourier transform. The target is accumulated in both the range and Doppler domains, effectively solving the problems caused by cross-range cell, Doppler broadening, and complex Doppler ambiguity.

[0052] This invention employs radial acceleration for searching, which makes it easier to obtain a coarse search range from the Doppler spectrum. A two-step search strategy is proposed: the first step is to obtain the search range, and the second step is a precise search with small step sizes. By utilizing a multi-stage search process, the search range decreases from large to small, and the search step size increases from coarse to fine, reducing the number of searches.

[0053] The method of this invention avoids high-dimensional parameter search operations and only performs a one-dimensional parameter matching search step for the maximum peak value of radial acceleration, which greatly reduces computational complexity.

[0054] Through efficient algorithm optimization, this invention significantly reduces computation time and resource consumption, thereby lowering computational costs without sacrificing simulation accuracy. This is of great significance for industrial applications that require fast and accurate simulations. Attached Figure Description

[0055] Figure 1 This is a flowchart of the present invention;

[0056] Figure 2 Figure 1 shows the results of linear span-range cell correction and velocity compensation for complex targets. Figure 2 shows the target trajectory of the original echo signal and Figure 3 shows the target trajectory after time reversal transformation.

[0057] Figure 3 This is a graph showing the result after the scaled inverse Fourier transform operation.

[0058] Figure 4 This is a graph showing the peak position information after the scaled inverse Fourier transform.

[0059] Figure 5 Figure 1 shows the cumulative distance-Doppler domain results before and after velocity compensation. Figure 2 shows the cumulative distance-Doppler domain results before and after velocity compensation. Figure 3 shows the cumulative distance-Doppler domain results before and after velocity compensation.

[0060] Figure 6This is a comparison chart of the detection probabilities of the present invention and the conventional method;

[0061] Figure 7 This is a comparison chart of the computational complexity of the present invention and traditional methods. Detailed Implementation

[0062] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0063] To address the issues of coherent cumulative loss caused by spanning range cells and Doppler spectral broadening, and the high computational complexity resulting from high-dimensional parameter search methods, this invention proposes a millimeter-wave radar moving target detection method based on scale-inverse Fourier processing. The overall architecture is as follows: Figure 1 As shown.

[0064] Scale inverse Fourier processing

[0065] 1. The distance-frequency-slow-time domain echo signal model is represented as:

[0066] (1)

[0067] Where s is about f and The function, where f is the frequency of the signal. These are slow-time variables; B is the bandwidth of the transmitted signal, c is the speed of electromagnetic wave propagation, and fc is the carrier frequency. This represents the instantaneous slant range between the target and the radar at the current slow time.

[0068] Using an improved time-reversal transform, the range-frequency-slow-time domain signal after target pulse compression is time-reversed and conjugated. The signal can be represented as:

[0069] (2)

[0070] in, This indicates a slow-time reversal operation, and * indicates a conjugate operation. In this case, the radial velocity and radial acceleration parameters of the target are separated, which can eliminate the influence of the slow-time quadratic term.

[0071] Performing a scaled inverse Fourier operation on the coupled distance frequency and slow time together yields:

[0072] (3)

[0073] in, This represents the distance-time after the inverse Fourier transform of the scale, where the distance frequency and slow time are decoupled, and the linear span-time unit is effectively corrected;

[0074] right Performing a slow-time Fourier transform yields:

[0075] (4)

[0076] in, This represents the scale frequency after SCIFT. Indicates the wavelength of the transmitted signal. It is the Dirac function.

[0077] The signal exhibits a distinct peak in the scaled frequency domain after the inverse Fourier operation, and the location of this peak can be used to obtain the target's radial velocity information.

[0078] ;

[0079] in, This indicates the peak position of the distance-time after the inverse Fourier scale operation.

[0080] After acquiring the target's radial velocity information, a phase compensation function is constructed to compensate for the target echo. The compensated result is as follows:

[0081] ;

[0082] in, Indicates the initial radial distance of the radar moving target. This indicates the radial acceleration of a moving target on radar.

[0083] The linear cross-distance cell phenomenon and Doppler blurring caused by radial velocity during the accumulation process were resolved.

[0084] Searching for radial acceleration

[0085] 1. Based on prior information or by setting the radial acceleration manually. maximum value Set the search scope to .

[0086] 2. Construct a phase compensation function for the matching search using the set radial acceleration cyclically:

[0087] ;

[0088] in, The velocity estimate can be obtained from the previous step using v.

[0089] Compensation is performed on the range-frequency-slow-time domain signal after target pulse compression to obtain the compensated result:

[0090] ;

[0091] At this time, the phase term of the target does not change with slow time, and energy defocusing will not occur.

[0092] By performing both slow-time Fourier transform and inverse Fourier transform in the range dimension, the matching search problem for radial acceleration can be transformed into a problem of maximizing the accumulated energy after target echo compensation. The radial acceleration with the largest energy peak within the search range is taken as the final search value.

[0093] ;

[0094] in, This represents performing an inverse Fourier transform on the signal based on its distance and frequency. This indicates a slow-time Fourier transform of the signal.

[0095] 4. After completing the search for radial acceleration, construct the coherent accumulation processing function:

[0096] ;

[0097] The result after completing coherent cumulative phase compensation is as follows:

[0098] ;

[0099] After phase compensation, the slow time and distance frequency are decoupled, effectively correcting the cross-distance cell phenomenon and also compensating for the Doppler broadening phenomenon.

[0100] Performing the inverse Fourier transform in the range domain and the Fourier transform in the slow time domain yields the final focusing result in the range-Doppler domain:

[0101] ;

[0102] in, The radial acceleration effect is compensated for by the coherent accumulation processing time of the radar system. The target is accumulated in both the range domain and the Doppler domain, effectively solving the effects of cross-range cell, Doppler broadening and complex Doppler ambiguity phenomena.

[0103] This invention proposes a scaled inverse Fourier method that, through a structured signal processing flow, can directly and accurately estimate the radial velocity of a moving target without parameter search. Utilizing an improved time-reversal transform, the slow-time quadratic term in the phase is eliminated by multiplying the signal with its time-reversed conjugate, thus separating the target's radial velocity from its radial acceleration parameters. The scaled inverse Fourier transform resolves the coupling between range frequency and slow time, effectively correcting linear range migration and forming an easily identifiable peak in the transformed domain that directly corresponds to the target's radial velocity.

[0104] This invention proposes a fast search method for radial acceleration. After obtaining the accurate radial velocity using the scaled inverse Fourier method, the motion parameter estimation problem is simplified to a one-dimensional search of radial acceleration, reducing computational complexity compared to multi-dimensional parameter searches. Secondly, it fully utilizes the characterization characteristics of radial acceleration on the Doppler spectrum. Compared to velocity, acceleration is easier to initially determine from the broadening and direction of the Doppler spectrum, making it more convenient and efficient to determine an effective coarse search range. Based on this, a two-step fast search strategy of "coarse to fine" is further proposed: first, a large step size is used to quickly locate the approximate range of acceleration, and then a small step size is used for precise matching within a smaller range. This strategy ensures estimation accuracy while minimizing unnecessary search iterations, further optimizing overall computational efficiency.

[0105] Based on this invention, the first step is a scale inverse Fourier processing operation. Figure 2 The results of linear span-range cell correction and velocity compensation for complex targets are presented. Figure 2 (a) shows the range-dimensional pulse compression result of the original target signal, where a more obvious cross-range cell phenomenon can be observed, and the bending is more severe compared to simple targets; Figure 2 (b) After the time reversal transformation, it can be seen that the target trajectory has become a straight line, indicating that the distance frequency and the slow time quadratic term have been decoupled and the linear cross-distance unit has been effectively corrected. Figure 3 The results after the scale-based inverse Fourier transform are shown. Since the simulation speed remained unchanged, the data from the 1334th Doppler cell was extracted, and the results are as follows. Figure 4 As shown. Finally, the radial velocity of the target is obtained from the range dimension position of this peak, and phase compensation is performed on the echo. The final accumulated result is as follows. Figure 5 As shown, it can be seen that after scale inverse Fourier processing, the target correction corrects the linear span-range cell and Doppler blurring phenomenon caused by radial velocity.

[0106] Figure 6 By comparing the detection probabilities of the present invention with those of the traditional MTD, RFT, and DPT methods under the same signal-to-noise ratio, it can be seen that the present invention addresses issues such as the cross-range cell phenomenon and Doppler broadening. The comparison of detection probability results shows that the proposed method has a better cumulative effect on moving targets than the MTD, RFT, and DPT methods. Figure 7 The computational complexity and pulse number relationship of this invention, the GRFT method, and the MKTMF method were compared. It can be seen that this invention avoids high-dimensional parameter search operations, and its computational complexity is significantly lower than that of the GRFT and MKTMF methods.

[0107] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

Claims

1. A method for detecting a moving target in a millimeter wave radar based on a scale inverse Fourier processing, characterized in that, Specifically: Echo signal in range frequency-slow time domain Performing time reversal transform processing to obtain an echo signal wherein denotes the range frequency, is a slow time variable, denotes a time reversal and conjugation operation function; Performing a joint frequency and slow-time inverse Fourier transform on yields , Performing a joint frequency and slow-time inverse Fourier transform on yields Performing a joint frequency and slow-time inverse Fourier transform on yields Extracting Peak value of distance-time in scale-frequency domain, target radial velocity is obtained based on peak value position ; Based on the obtained target radial velocity, the phase compensation function is constructed to compensate the phase error of the target radial velocity After the compensation, one-dimensional search is performed in the set radial acceleration search range to obtain an estimated value of the target radial acceleration. Relevant information about the target can be extracted by the target's radial velocity; or relevant information about the target can be extracted by the target's radial acceleration. The relevant information includes information other than the target's radial velocity and radial acceleration, such as target detection, trajectory, or position.

2. The millimeter wave radar moving target detection method based on scale inverse Fourier processing according to claim 1, characterized in that, The time reversal transform involves performing time reversal and conjugation operations on the echo signal, specifically: ； where * denotes a conjugate operation, denotes a slow-time reversal of ; The expression for is: ； where B is the bandwidth of the transmitted signal, c is the speed of electromagnetic wave propagation, is the carrier frequency, denotes the current slow time the instantaneous slant range between the target and the radar.

3. The millimeter-wave radar moving target detection method based on scale inverse Fourier processing according to claim 1, characterized in that, The pair Perform a joint scaling Fourier transform on both frequency and slow-time parameters, specifically: [The text abruptly ends here, likely due to an incomplete sentence or a formatting error.] Perform a scaling Fourier transform along the frequency dimension: ； Where B is the bandwidth of the transmitted signal, and c is the speed of electromagnetic wave propagation. This is the carrier frequency; Then to Perform a scaling Fourier transform in the slow time dimension: ； in, Indicates the wavelength of the transmitted signal. It is the Dirac function.

4. The millimeter-wave radar moving target detection method based on scale inverse Fourier processing according to claim 1, characterized in that, The target radial velocity is obtained based on the peak position, specifically as follows: ； Where c is the speed of electromagnetic wave propagation. This represents the location of the peak value over time.

5. The millimeter-wave radar moving target detection method based on scale inverse Fourier processing according to claim 1, characterized in that, The specific steps to obtain the estimated value of the target's radial acceleration are as follows: Set the maximum value of radial acceleration. Set the search range based on the maximum value; Set a fixed step size to extract acceleration sampling points within the search range; Construct a phase compensation function for each sampling point : ； in, The acceleration value corresponding to the velocity sampling point. The velocity estimate can be v, where c is the speed of electromagnetic wave propagation. For carrier frequency; Based on the phase compensation function Perform phase compensation: ； in, The echo signal after phase compensation; Perform a slow-time Fourier transform and a frequency-time inverse Fourier transform on all phase-compensated echo signals. Select the radial acceleration with the largest energy peak from the echo signals after the inverse Fourier transform as the optimal radial acceleration.

6. The millimeter-wave radar moving target detection method based on scale inverse Fourier processing according to claim 5, characterized in that, The search scope is set as follows .

7. The millimeter-wave radar moving target detection method based on scale inverse Fourier processing according to claim 5, characterized in that, Extracting relevant target information using radial acceleration involves: constructing a coherent accumulation processing function based on radial acceleration. ； The echo signal is compensated using a coherent cumulative processing function: ； in, For the compensated echo signal, The wavelength of the transmitted signal; right Perform inverse Fourier transform in the frequency dimension and Fourier transform in the slow time dimension; based on the transformed echo signal, extract other information about the target: ； in, This is the coherent cumulative processing time for the radar system.

8. The millimeter-wave radar moving target detection method based on scale inverse Fourier processing according to claim 1, characterized in that, Extracting other information about the target by means of the target radial velocity involves: after obtaining the target radial velocity, constructing a phase compensation function to compensate the echo signal, and extracting relevant target information based on the compensated echo signal.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the millimeter-wave radar moving target detection method based on scale inverse Fourier processing as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the millimeter-wave radar moving target detection method based on scale inverse Fourier processing as described in any one of claims 1 to 8.

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