Signal processing method and signal processing equipment of step frequency radar and computer readable storage medium

Abstract

The invention relates to a step frequency radar signal processing method, a step frequency radar signal processing device and a computer readable storage medium. The signal processing method comprises the following steps: S1, sampling M points in the time width of each chirp signal, wherein the total number of sampling points is M * N; generating a two-dimensional array x (i, j); s2, carrying out distance dimension FFT (Fast Fourier Transform) on the two-dimensional array x (i, j); carrying out FFT (Fast Fourier Transform) of a speed dimension; s3, accumulating Mag values of the converted signals; s4, performing CFAR processing on the accumulated signal to obtain a peak target, wherein k targets are arranged; s5, calculating the phase difference of the signals at the position index k, and calculating the real Doppler of the target at the position index k; s6, calculating the real distance of the target at the position index k; and S7, calculating the real speed of the target at the position index k. The distance and the speed of the target can be effectively obtained.

Description

Technical Field

[0001] The present invention relates to the field of radar signal processing technology, and in particular to a signal processing method, a signal processing device and a computer-readable storage medium for a stepped frequency radar. Background Art

[0002] As a broadband radar signal, the stepped frequency signal can achieve high range resolution through the method of coherent pulse synthesis. The specific process is as follows: First, a group of narrowband single-carrier frequency pulses are transmitted in sequence, and the carrier frequency of each pulse is evenly stepped. When receiving, the echo signal of this group of pulses is mixed with the local oscillator signal corresponding to the carrier frequency. The zero intermediate frequency signal after mixing can obtain a group of complex sampling values ​​of the target echo through orthogonal sampling. By performing an inverse discrete Fourier transform (IDFT) on this group of complex sampling signals, a high-resolution range image of the target can be obtained. In essence, it is to sample the target echo in the frequency domain and then calculate its time domain echo. The time domain sampling is achieved by transmitting a discrete frequency step signal. Since the single pulse signal processed by the coherent synthesis of multiple pulses is a signal with a narrow bandwidth, the requirements for system bandwidth and sampling rate are greatly reduced, which is conducive to engineering implementation.

[0003] Traditional vehicle-mounted radars usually use frequency modulated continuous wave waveforms, which transmit sawtooth wave signals and process the received echo signals to obtain the target distance and speed. Ultra-high distance resolution requires a large bandwidth, which makes the system bandwidth and sampling rate requirements relatively high.

[0004] Therefore, the stepped frequency and linear frequency modulation can be combined, so that the frequency modulation bandwidth in each pulse can be reduced while ensuring the performance of the linear frequency modulation radar, and at the same time, ultra-high distance resolution can be obtained. However, for moving targets, the relative motion will cause distance-velocity coupling, and the distance and speed of the target cannot be accurately obtained. Existing technologies usually use the correlation between different frame data to estimate the target speed, or estimate the speed first, use the estimated speed for motion compensation, and then calculate the distance. However, these current methods have the disadvantages of large amount of calculation, large impact on data stability, easy error in inter-frame data association, and large estimation error. Summary of the invention

[0005] In view of the above problems in the prior art, the present invention proposes a signal processing method, a signal processing device and a computer-readable storage medium for a stepped frequency radar, which can effectively obtain the distance and speed of the target and is suitable for the detection of multiple moving and static targets.

[0006] Specifically, the present invention proposes a signal processing method for a stepped frequency radar, wherein the transmitting end of the stepped frequency radar transmits a sawtooth wave with a stepped frequency, the initial frequency is f0, the frequency step is △f, the period is T, the linear frequency modulation bandwidth B1 within the pulse, the synthetic total bandwidth B2, the sequential transmission time widths are T1, T2 and T3, representing the chirp signals of the A wave, the B wave and the C wave respectively, and the total number of chirp signals transmitted in one frame is N; the signal processing method of the receiving end of the stepped frequency radar comprises the following steps:

[0007] S1, sample M points within the time width of each chirp signal, then the total number of sampling points is M*N; perform analog-to-digital conversion on the collected signal to generate a two-dimensional array x(i,j), 1≤i≤M, 1≤j≤N;

[0008] S2, first perform FFT transformation of the distance dimension on the two-dimensional array x(i,j) to generate the array S1(i,j), 1≤i≤M / 2, 1≤j≤N; then perform FFT transformation of the velocity dimension on S1(i,j), based on the different waveforms of the A wave, B wave and C wave, the generated signals after FFT transformation are S2A(i,j), S2B(i,j), S2C(i,j), 1≤i≤M / 2, 1≤j≤N / 3;

[0009] S3, accumulate the Mag values ​​of S2A(i,j), S2B(i,j), and S2C(i,j), and record the accumulated RDM as S(i,j), 1≤i≤M / 2, 1≤j≤N / 3;

[0010] S4, after CFAR processing S(i,j), the peak target is obtained. Suppose there are k targets, and the detected target distance dimension index numbers are r1, r2, ...rk, and the speed dimension index numbers are d1, d2, ...dk;

[0011] S5, calculate the phase difference of the signal at position index k, and calculate the real doppler bin of the target at position index k;

[0012] S6, calculate the true distance of the target at position index k;

[0013] S7, calculate the true speed of the target at position index k.

[0014] According to one embodiment of the present invention, the synthesized total bandwidth B2 = (N / 3-1)*Δf.

[0015] According to one embodiment of the present invention, in step S5, calculating the phase difference of the signal at the position index k includes:

[0016] Get the signal values ​​corresponding to different waveforms at the target location index K, chA = S2A (rk, dk), chB = S2B (rk, dk), chC = S2C (rk, dk);

[0017] The calculation formula of phase difference is:

[0018] phiBA = angle(chB / chA);

[0019] phiCB=angle(chC / chB).

[0020] According to one embodiment of the present invention, the calculation formula for calculating the true doppler bin of the target at position index k is:

[0021] Lambda = 3e8 / (f0+B2 / 2);

[0022] para_f=4*3.1415926*T2 / Lambda;

[0023] Vres=3e8 / 2 / (T1+T2+T3) / (f0+B2 / 2) / N*3;

[0024] Vc = phiBA / para_f;

[0025] dopplerbin=round(Vc / Vres);

[0026] Among them, the variable Lambda is the wavelength, 3e8 is the speed of light, the variable para_f is the intermediate calculation amount, the variable Vres is the speed resolution, the variable Vc is the estimated speed of the target, and the round function is used to round off.

[0027] According to one embodiment of the present invention, in step S6, the calculation formula for calculating the real distance of the target at the position index k is:

[0028] range_res0 = 3e8 / (2*B1);

[0029] range_res1 = 3e8 / (2*B2);

[0030] Rdopplerbin=dk-dopplerbin;

[0031] offset=mod((rk-1)*range_res0 / range_res1,N / 3)+1;

[0032] R=(rk-1)*range_res0+(Rdopplerbin-offset)*range_res1;

[0033] Among them, range_res0 represents the distance resolution based on the linear frequency modulation bandwidth B1 within the pulse, ange_res1 represents the distance resolution based on the synthetic total bandwidth B2, dk is the index number of the target in the velocity dimension, Rdopplerbin is used to characterize the difference between the target and the Doppler unit in the velocity dimension, the variable offset represents the offset, rk is the index number of the target in the distance dimension, and R is the actual distance value of the target.

[0034] According to one embodiment of the present invention, in step S7, the real speed of the target at the position index k is solved based on the phase difference and the real distance of the signal at the position index k.

[0035] The present invention also provides a signal processing device for a stepped frequency radar, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the aforementioned signal processing methods when executing the computer program.

[0036] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the signal processing method described in any one of the above items are implemented.

[0037] The present invention provides a signal processing method, a signal processing device and a computer-readable storage medium for a stepped frequency radar. A plurality of chirp signals with different waveforms are configured at a transmitting end, and sampling is performed at a receiving end within the time width of each chirp signal. An FFT transform of the distance dimension is performed, and then an FFT transform of the speed dimension is performed. After CFAR processing, a peak target is obtained, and then the phase difference of the signal at a position index k is calculated, and the real dopplerbin of the target at the position index k is calculated. Finally, the real distance and speed of the target are obtained, so that it is suitable for the detection of multiple moving and static targets.

[0038] It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings are included to provide further explanation of the present invention, and are incorporated into and constitute a part of this application. The accompanying drawings illustrate embodiments of the present invention and together with the description serve to explain the principle of the present invention.

[0040] In the attached figure:

[0041] Figure 1 The figure shows a transmission waveform diagram of a stepped frequency radar transmitting end according to an embodiment of the present invention.

[0042] Figure 2 A flowchart of a signal processing method for a stepped frequency radar according to an embodiment of the present invention is shown.

[0043] Figure 3 A schematic diagram showing a signal processing method for a stepped frequency radar according to an embodiment of the present invention simulating two targets is shown. DETAILED DESCRIPTION

[0044] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other.

[0045] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present application and its application or use. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0046] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0047] Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values ​​of the parts and steps set forth in these embodiments do not limit the scope of the application. Meanwhile, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to actual proportional relationships. The technology, methods and equipment known to those of ordinary skill in the relevant art may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be considered as a part of the specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0048] In the description of the present application, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction, and therefore cannot be understood as limiting the scope of protection of the present application; the directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.

[0049] In addition, it should be noted that the use of words such as "first" and "second" to define components is only for the convenience of distinguishing the corresponding components. If not otherwise stated, the above words have no special meaning and cannot be understood as limiting the scope of protection of this application. In addition, although the terms used in this application are selected from well-known and commonly used terms, some terms mentioned in the specification of this application may be selected by the applicant at his or her discretion, and their detailed meanings are explained in the relevant parts of the description of this article. In addition, it is required to understand this application not only by the actual terms used, but also by the meaning implied by each term.

[0050] Figure 1 The figure shows a transmission waveform diagram of a stepped frequency radar transmitting end according to an embodiment of the present invention. Figure 2 The flowchart of the signal processing method of the stepped frequency radar according to one embodiment of the present invention is shown. The present invention provides a signal processing method of the stepped frequency radar. Figure 1 , the radar transmits a frequency-stepped sawtooth wave. The initial frequency is f0, the frequency step is △f, the period is T, the linear frequency modulation bandwidth within the pulse is B1, the total synthesis bandwidth is B2, and the sequential transmission time widths are T1, T2 and T3, representing the chirp signals of wave A, wave B and wave C respectively. The total number of chirp signals transmitted in one frame is N, then the number of chirp signals transmitted for wave A, wave B and wave C is N / 3 each. Figure 2 As shown, the signal processing method at the radar receiving end includes the following steps:

[0051] S1, sample M points within the time width of each chirp signal, then the total number of sampling points is M*N; perform analog-to-digital conversion on the collected signal to generate a two-dimensional array x(i,j), 1≤i≤M, 1≤j≤N. The size of M is related to whether the waveform details of each chirp signal in the time domain can be accurately depicted. More sampling points can more clearly show the changes of the signal over time. In other words, the more sampling points there are, the higher the frequency domain resolution will be when the sampled signal is subsequently analyzed in the frequency domain, and the true spectrum structure of each chirp signal can be obtained more accurately, so as to better analyze its frequency modulation and other characteristics, which is conducive to the subsequent judgment of relevant information of the target.

[0052] S2, first perform FFT transformation of the two-dimensional array x(i,j) in the distance dimension to generate the array S1(i,j), 1≤i≤M / 2, 1≤j≤N; then perform FFT transformation of S1(i,j) in the velocity dimension. Based on the different waveforms of A wave, B wave and C wave, they need to be processed separately, that is, S1(i,1), S1(i,4), S1(i,j) are A wave, S1(i,2), S1(i,5), S1(i,j+1) are B wave, S1(i,3), S1(i,6), S1(i,j+2) are C wave, perform FFT transformation of N / 3 points on each distance dimension, and the signals after FFT transformation are S2A(i,j), S2B(i,j), S2C(i,j), 1≤i≤M / 2, 1≤j≤N / 3. Since the characteristics of radar signals in the time domain are closely related to the distance information of the target, the time domain signal can be converted to the frequency domain through the FFT transform of the distance dimension, and then the relevant characteristic information that can reflect the target distance can be extracted from it. Since the target speed characteristics corresponding to different waveforms may be different, the A wave, B wave and C wave must be processed separately. Through the speed dimension FFT transform, the frequency domain characteristics related to the target speed can be further mined on the basis of the distance dimension transform.

[0053] S3, accumulate the Mag values ​​of S2A(i,j), S2B(i,j), and S2C(i,j), and record the accumulated RDM as S(i,j), 1≤i≤M / 2, 1≤j≤N / 3. Mag value usually refers to the amplitude of the signal. In radar signal processing, by accumulating Mag values, the signal characteristics of the target in the entire frequency domain can be enhanced, making those target signal characteristics that may have been relatively weak or less obvious more prominent, which helps to improve the accuracy of subsequent target detection and recognition.

[0054] S4, after CFAR processing S(i,j), the peak target is obtained. Suppose there are k targets, and the detected target distance dimension index numbers are r1, r2, ...rk, and the speed dimension index numbers are d1, d2, ...dk. In radar signal processing, factors such as background clutter and noise will interfere with the accurate detection of the target. The main purpose of CFAR processing is to adaptively adjust the detection threshold in a complex radar echo environment so that the false alarm probability (that is, the probability of misjudging noise or clutter as a target) is maintained at a relatively constant level, so that the real target signal can be reliably screened out from many signals. After CFAR processing, in the two-dimensional space of S(i,j), those local maximum points that are significantly higher than the threshold are identified as the peak points corresponding to the target. The locations of these peak points reflect the characteristic information of the target in the distance dimension and the speed dimension.

[0055] S5, calculates the phase difference of the signal at position index k, and calculates the real dopplerbin of the target at position index k. In the radar system, the phase difference is closely related to the target distance. The transmitted signal is reflected back after encountering the target. In this process, the distance and phase change of the signal propagation are related. For the signal at position index k, calculating its phase difference can use this correlation to obtain the target distance information. Obtaining the real Dopplerbin can accurately quantify the target speed and locate the target speed to a specific speed range.

[0056] S6, calculating the real distance of the target at position index k. The real distance of the target at position index k is calculated based on the phase difference of the signal at position index k.

[0057] S7, calculating the true speed of the target at position index k. The true speed of the target at position index k is calculated based on the phase difference of the signal at position index k.

[0058] In some examples, the composite total bandwidth B2 = (N / 3-1)*Δf.

[0059] In some examples, in step S5, calculating the phase difference of the signal at position index k comprises the steps of:

[0060] Get the signal values ​​corresponding to different waveforms at the target location index K, chA = S2A (rk, dk), chB = S2B (rk, dk), chC = S2C (rk, dk). The three variables chA, chB and chC represent the values ​​corresponding to the location index K extracted from the signal data related to different waveforms obtained after the previous series of processing.

[0061] The calculation formula of phase difference is:

[0062] phiBA=angle(chB / chA), the phase difference between the B wave and the A wave at position index K is obtained.

[0063] phiCB=angle(chC / chB), the phase difference between the C wave and the B wave at position index K is obtained.

[0064] In some examples, the formula for calculating the true doppler bin of a target at position index k is:

[0065] Lambda=3e8 / (f0+B2 / 2); variable Lambda is the wavelength, 3e8 is the speed of light, f0 is the initial frequency, B2 is the total synthetic bandwidth, and (f0+B2 / 2) means that the corresponding wavelength value is calculated by comprehensively considering the frequency factor.

[0066] para_f=4*3.1415926*T2 / Lambda; the variable para_f is the intermediate calculation quantity, T2 is the emission time width of the B wave, and the variable para_f is used to establish the connection between the waveform time parameter and the wavelength, in preparation for the subsequent calculation of the target speed.

[0067] Vres=3e8 / 2 / (T1+T2+T3) / (f0+B2 / 2) / N*3; variable Vres is the velocity resolution, T1, T2 and T3 represent the transmission time width of wave A, wave B and wave C respectively, N is the total number of chirp signals transmitted in one frame, and the velocity resolution reflects the precision of the radar system in distinguishing targets of different speeds, which subsequently determines how to divide the continuous velocity values ​​into discrete Doppler bins.

[0068] Vc=phiBA / para_f; variable Vc is the estimated value of the target speed, phiBA is the phase difference between the B wave and the A wave at position index K, and variable Vc is an intermediate calculation result of the target speed.

[0069] dopplerbin=round(Vc / Vres), where the round function is used to round off the target velocity estimate Vc according to the velocity resolution Vres to determine in which discrete Dopplerbin the target falls.

[0070] In some examples, in step S6, the calculation formula for calculating the actual distance of the target at the position index k is:

[0071] range_res0=3e8 / (2*B1); range_res0 represents the distance resolution based on the intra-pulse linear frequency modulation bandwidth B1.

[0072] range_res1=3e8 / (2*B2); range_res1 represents the range resolution based on the synthetic total bandwidth B2. These two range resolution parameters are important basic quantities for the subsequent calculation of the target's true distance. By combining with other key information such as the target's index number in the distance dimension and speed dimension, the target's actual accurate distance can be gradually calculated. Different range resolutions are used to adapt to different signal characteristics and calculation links, so as to more accurately restore the target's true distance.

[0073] Rdopplerbin=dk–dopplerbin; where dk is the index number of the target in the velocity dimension, which represents the relative position number of the target in the velocity dimension after a series of signal processing. This number can reflect the characteristic information of the target in the velocity dimension. dopplerbin is the Doppler unit number of the previously determined target. The two are subtracted to obtain the variable Rdopplerbin, which is used to characterize the difference between the target in the velocity dimension and the Doppler unit, and to establish the association between the target position information in the velocity dimension and the Doppler unit information.

[0074] offset=mod((rk-1)*range_res0 / range_res1,N / 3)+1; rk is the index of the target in the distance dimension, N / 3 is the number of chirp signals with different waveforms, and the mod function represents the modulo operation. The variable offset plays a correction and adjustment role in calculating the actual distance of the target.

[0075] R = (rk-1)*range_res0+(Rdopplerbin-offset)*range_res1; (rk-1)*range_res0 is a basic distance calculation based on the target's index number rk in the distance dimension and the distance resolution range_res0. The approximate distance range of the target is preliminarily determined according to the relative position of the target in the distance dimension. (Rdopplerbin-offset)*range_res1 is a distance adjustment calculation that combines Rdopplerbin, offset and another distance resolution range_res1 related to the speed dimension. The two parts are added together to obtain the actual distance value of the target.

[0076] In some examples, in step S7, based on the phase difference of the signal at position index k, the velocity ambiguity is resolved by using the remainder. Specifically, based on the previously derived related formulas, including wavelength, calculation formulas related to the Doppler effect, etc., a mathematical relationship model between the phase difference phiBA, phiCB and the target velocity is established. The phiBA and phiCB values ​​actually measured are substituted into the established relationship model to solve the remainder. Finally, based on the remainder, the true velocity is determined.

[0077] Figure 3 The schematic diagram of the signal processing method of the stepped frequency radar of an embodiment of the present invention is shown to simulate two targets. In this embodiment, the radar transmitter transmits a frequency-stepped sawtooth wave. When the transmitter transmits the waveform, the initial frequency f0=76GHz, the frequency step length △f=2.941MHz, the A wave transmission time width T1=17.2μs, the B wave transmission time width T2=25.8μs, the C wave transmission time width T3=39.3μs, the total number of chirp signals transmitted in one frame N=768, the frequency modulation bandwidth B1=93.75MHz, and the synthesized total bandwidth B2=(N / 3-1)*△f=749.955MHz. Simulate two targets R1=11.2m, V1=0m / s, R2=11.2m, V2=5m / s. The signal processing steps at the receiving end are as follows:

[0078] S1, sample M = 256 points in the time width of each chirp, then the total number of sampling points is 256*768; perform analog-to-digital conversion on the collected signal, generate ADC data, 256 sampling points as a group, a total of 768 chirps are emitted, forming a two-dimensional array x(i,j), 1≤i≤256, 1≤j≤768;

[0079] S2, first perform FFT transformation of the distance dimension on the two-dimensional array x, that is, perform 256-point FFT transformation on each chirp, and record the transformed signal as S1(i,j), 1≤i≤128, 1≤j≤768; then perform FFT transformation of S1(i,j) in the velocity dimension, because there are three different T waveforms in the velocity dimension, which need to be processed separately, that is, S1(i,1), S1(i,4), S1(i,j) are A waves , S1(i,2), S1(i,5), S1(i,j+1) are B waves, S1(i,3), S1(i,6), S1(i,j+2) are C waves, 1≤i≤128, 1≤j≤766; that is, a 256-point FFT transformation is performed on each distance dimension, and the transformed signals are recorded as S2A(i,j), S2B(i,j), S2C(i,j), 1≤i≤128, 1≤j≤256;

[0080] S3, accumulate the Mag values ​​of S2A(i,j), S2B(i,j), and S2C(i,j), and record the accumulated RDM as S(i,j), 1≤i≤128, 1≤j≤256;

[0081] S4, after CFAR processing of RDM, i.e. S(i,j), the peak target is obtained, and two targets are detected. The distance dimension index number of target 1 is r1=8, and the speed dimension index number is d1=57; the distance dimension index number of target 2 is r2=8, and the speed dimension index number is d2=111;

[0082] S5 to S6, calculate the true doppler bin and true distance of target 1, the calculation formula is as follows:

[0083] chA=S2A(8,57)=-3.8305e6-9.3284e5i,

[0084] chB=S2B(8,57)=-3.8300e6-9.3365e5i,

[0085] chC=S2C(8,57)=-3.8300e6-9.3253e5i,

[0086] phiBA=angle(chB / chA)=2.3172e-4,

[0087] phiCB=angle(chC / chB)=-2.7998e-4,

[0088] para_f=0.0825; Vres=0.0932;

[0089] Vc = phiBA / para_f = 0.0028;

[0090] dopplerbin=round(Vc / Vres)=0;

[0091] range_res0=3e8 / (2*B1)=1.6;

[0092] range_res1=3e8 / (2*B2)=0.2;

[0093] Rdopplerbin=d1-dopplerbin=57;

[0094] offset=mod((r1-1)*range_res0 / range_res1,N / 3)+1=56.9966;

[0095] R=(r1-1)*range_res0+(Rdopplerbin-offset)*range_res1=11.2007.

[0096] Repeat steps S5 to S6 to calculate the true doppler bin and true distance of target 2. The calculation formula is as follows:

[0097] chA=S2A(8,111)=-3.4780e6+1.9641e6i,

[0098] chB=S2B(8,111)=-3.9734e6+4.0422e6i,

[0099] chC=S2C(8,111)=-3.4510e6-2.0092e6i,

[0100] phiBA=angle(chB / chA)=0.4127,

[0101] phiCB=angle(chC / chB)=0.6286,

[0102] Vc = phiBA / para_f = 4.9998;

[0103] dopplerbin=round(Vc / Vres)=54;

[0104] Rdopplerbin=d2-dopplerbin=57;

[0105] offset=mod((r2-1)*range_res0 / range_res1,N / 3)+1=56.9966;

[0106] R=(r2-1)*range_res0+(Rdopplerbin-offset)*range_res1=11.2007.

[0107] S7, based on the phase difference and true distance of the signal at the position index, solve the true speed of the target at the position index k.

[0108] The present invention also provides a signal processing device for a stepped frequency radar, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the aforementioned signal processing methods when executing the computer program.

[0109] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned signal processing methods are implemented.

[0110] Among them, the specific implementation methods and technical effects of the signal processing equipment and computer-readable storage medium of the stepped frequency radar can be referred to the embodiments of the detection method provided by the above-mentioned present invention, and will not be repeated here.

[0111] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or a combination of the two. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps are generally described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. The technician may implement the described functionality in different ways for each specific application, but such implementation decisions should not be interpreted as resulting in a departure from the scope of the present invention.

[0112] The various illustrative logic modules and circuits described in conjunction with the embodiments disclosed herein may be implemented or executed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in cooperation with a DSP core, or any other such configuration.

[0113] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read and write information from / to the storage medium. In an alternative, a storage medium may be integrated into a processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and the storage medium may reside in a user terminal as discrete components.

[0114] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented as a computer program product in software, each function may be stored on or transmitted by a computer-readable medium as one or more instructions or codes. Computer-readable media include both computer storage media and communication media, including any medium that facilitates the transfer of a computer program from one place to another. Storage media may be any available medium that can be accessed by a computer. As an example and not limitation, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer. Any connection is also properly referred to as a computer-readable medium. For example, if the software is transmitted from a website, a server, or other remote source using a coaxial cable, a fiber optic cable, a twisted pair, a digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of the medium. Disk and disc as used herein include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, wherein disk often reproduces data magnetically, while disc reproduces data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0115] It will be apparent to those skilled in the art that various modifications and variations may be made to the above exemplary embodiments of the present invention without departing from the spirit and scope of the present invention. Therefore, it is intended that the present invention covers modifications and variations of the present invention that fall within the scope of the appended claims and their equivalent technical solutions.

Claims

1. A signal processing method for a stepped frequency radar, wherein the transmitting end of the stepped frequency radar transmits a sawtooth wave with a stepped frequency, the initial frequency is f0, the frequency step is △f, the period is T, the linear frequency modulation bandwidth within the pulse is B1, the total synthesis bandwidth is B2, the sequential transmission time widths are T1, T2 and T3, representing the chirp signals of the A wave, the B wave and the C wave respectively, and the total number of chirp signals transmitted in one frame is N; the signal processing method of the receiving end of the stepped frequency radar comprises the following steps: S1, sample M points within the time width of each chirp signal, then the total number of sampling points is M*N; perform analog-to-digital conversion on the collected signal to generate a two-dimensional array x(i,j), 1≤i≤M, 1≤j≤N; S2, first perform FFT transformation of the distance dimension on the two-dimensional array x(i,j) to generate the array S1(i,j), 1≤i≤M / 2, 1≤j≤N; then perform FFT transformation of the velocity dimension on S1(i,j), based on the different waveforms of the A wave, B wave and C wave, the generated signals after FFT transformation are S2A(i,j), S2B(i,j), S2C(i,j), 1≤i≤M / 2, 1≤j≤N / 3; S3, accumulate the Mag values ​​of S2A(i,j), S2B(i,j), and S2C(i,j), and record the accumulated RDM as S(i,j), 1≤i≤M / 2, 1≤j≤N / 3; S4, after CFAR processing S(i,j), the peak target is obtained. Suppose there are k targets, and the detected target distance dimension index numbers are r1, r2, ...rk, and the speed dimension index numbers are d1, d2, ...dk; S5, calculate the phase difference of the signal at position index k, and calculate the real doppler bin of the target at position index k; S6, calculate the true distance of the target at position index k; S7, calculate the true speed of the target at position index k.

2. The signal processing method of the stepped frequency radar as claimed in claim 1, characterized in that: The total composite bandwidth B2 = (N / 3-1)*Δf.

3. The signal processing method of the stepped frequency radar as claimed in claim 1, characterized in that: In step S5, calculating the phase difference of the signal at position index k includes: Get the signal values ​​corresponding to different waveforms at the target location index K, chA = S2A (rk, dk), chB = S2B (rk, dk), chC = S2C (rk, dk); The calculation formula of phase difference is: phiBA = angle(chB / chA); phiCB=angle(chC / chB).

4. The signal processing method of the stepped frequency radar as claimed in claim 3, characterized in that: The formula for calculating the true doppler bin of the target at position index k is: Lambda = 3e8 / (f0+B2 / 2); para_f=4*3.1415926*T2 / Lambda; Vres=3e8 / 2 / (T1+T2+T3) / (f0+B2 / 2) / N*3; Vc = phiBA / para_f; dopplerbin=round(Vc / Vres); Among them, the variable Lambda is the wavelength, 3e8 is the speed of light, the variable para_f is the intermediate calculation amount, the variable Vres is the speed resolution, the variable Vc is the estimated speed of the target, and the round function is used to round off.

5. The signal processing method of the stepped frequency radar as claimed in claim 4, characterized in that: In step S6, the calculation formula for calculating the actual distance of the target at position index k is: range_res0 = 3e8 / (2*B1); range_res1 = 3e8 / (2*B2); Rdopplerbin=dk-dopplerbin; offset=mod((rk-1)*range_res0 / range_res1,N / 3)+1; R=(rk-1)*range_res0+(Rdopplerbin-offset)*range_res1; Among them, range_res0 represents the distance resolution based on the linear frequency modulation bandwidth B1 within the pulse, ange_res1 represents the distance resolution based on the synthetic total bandwidth B2, dk is the index number of the target in the velocity dimension, Rdopplerbin is used to characterize the difference between the target and the Doppler unit in the velocity dimension, the variable offset represents the offset, rk is the index number of the target in the distance dimension, and R is the actual distance value of the target.

6. The signal processing method of the stepped frequency radar as claimed in claim 1, characterized in that: In step S7, the real speed of the target at position index k is solved based on the phase difference and real distance of the signal at position index k.

7. A signal processing device for a stepped frequency radar, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the signal processing method according to any one of claims 1 to 6 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the signal processing method according to any one of claims 1 to 6 are implemented.

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