Speed ambiguity resolution method, device and equipment of DDM MIMO-OFDM radar and storage medium

Abstract

The invention relates to the technical field of radars, and discloses a speed ambiguity resolution method, device and equipment for a DDM MIMO-OFDM radar and a storage medium, and the method comprises the steps: constructing a radar orthogonal transmission signal according to a preset Doppler division multiplexing phase; constructing a target echo signal based on the transmitting signal, and preprocessing the echo signal to obtain a discrete echo signal corresponding to a single receiving antenna; performing discrete Fourier transform and matrix division on the discrete echo signal to obtain a radar channel matrix containing target distance and speed information; performing distance dimension inverse discrete Fourier transform and speed dimension discrete Fourier transform on the radar channel matrix to obtain a target distance-speed image; performing peak detection on the target distance-speed image to obtain a plurality of peaks of the same target, obtaining a speed index difference of adjacent peaks based on the peaks, and determining a speed fuzzy number; the real speed of the target can be estimated, and the target overlapping problem is effectively solved.

Description

Technical Field

[0001] The present invention relates to the field of radar technology, and in particular to a velocity deambiguation method, device, equipment and storage medium for a DDM MIMO-OFDM radar. Background Art

[0002] Multiple Input Multiple Output (MIMO) radar constructs virtual array elements through orthogonal waveforms, which can achieve high angular resolution with a limited number of antennas. Orthogonal Frequency Division Multiplex (OFDM) is a multi-carrier transmission technology commonly used in modern communications. It has the advantages of large time-bandwidth product, flexible parameter design, and good anti-interception performance. Combining OFDM with MIMO radar can achieve high-resolution ranging and high-precision angle measurement.

[0003] Multiple-input multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM) radar uses the Doppler-division multiplexing (DDM) method to separate the target echoes from different transmitting antennas in the Doppler domain (velocity domain) by adding different phases between adjacent OFDM symbols of different transmitting antennas. However, the DDM method reduces the maximum unambiguous speed and produces a speed ambiguity problem. The existing empty-band speed deambiguation method is to insert an empty band on the velocity spectrum and estimate the true speed of the target by energy accumulation. However, when multiple targets are at the same distance and the speed difference is an integer multiple of the maximum unambiguous speed, the existing empty-band speed deambiguation method will have a target overlap problem.

[0004] Therefore, there is an urgent need for a velocity deambiguation method for DDM MIMO-OFDM radar that can overcome the defects of the existing technical solutions, estimate the true speed of the target, and effectively solve the target overlap problem. Summary of the invention

[0005] In view of this, the present application provides a speed deambiguation method, device, equipment and storage medium for a DDM MIMO-OFDM radar, which can estimate the true speed of a target and effectively solve the problem of target overlap. The technical solution is as follows.

[0006] In a first aspect, the present invention provides a velocity deambiguation method for a DDM MIMO-OFDM radar, wherein the MIMO-OFDM radar includes a plurality of transmitting antennas and receiving antennas, and the method includes:

[0007] Constructing radar orthogonal transmission signals according to the preset Doppler multiplexing phase;

[0008] Based on the transmission signal, a target echo signal is constructed, and the target echo signal is preprocessed to obtain a discrete echo signal corresponding to a single receiving antenna;

[0009] Performing discrete Fourier transform and matrix division on the discrete echo signal to obtain a radar channel matrix containing target distance and speed information;

[0010] Performing a distance-dimensional inverse discrete Fourier transform and a velocity-dimensional discrete Fourier transform on the radar channel matrix to obtain a target range-velocity image;

[0011] Peak detection is performed on the target range-speed image to obtain a plurality of peaks of the same target on the target range-speed image, and speed index differences of adjacent peaks are obtained based on the peaks, and speed fuzzy numbers are determined based on the speed index differences.

[0012] In an optional implementation, the radar orthogonal transmission signal is constructed according to a preset Doppler multiplexing phase, including:

[0013] Adding an offset phase to the Doppler multiplexing phase to obtain the phase of each transmitting antenna;

[0014] Based on the phase, construct the transmission signal of each transmitting antenna;

[0015] Among them, the expression of the phase of each transmitting antenna is:

[0016]

[0017] Where k represents the kth transmitting antenna, and are the Doppler multiplexing phase and the added offset phase of the kth transmitting antenna respectively;

[0018] The expression of the signal transmitted by the kth transmitting antenna is:

[0019]

[0020] Where N s and N c are the number of OFDM symbols and subcarrier frequencies respectively; S(n,m) is the communication information carried by the nth subcarrier frequency on the mth OFDM symbol; T s =T+T g is a complete OFDM symbol period; T = 1 / Δf is the effective OFDM symbol period; Δf is the subcarrier frequency interval; T g is the cyclic prefix period; rect(t / T s ) is a rectangular window function, when 0 <t<T s 1 when , otherwise 0; fc For the carrier frequency.

[0021] In an optional implementation, the expression of the discrete echo signal is:

[0022]

[0023] Where i = 0,…,N c -1, indicating fast time dimension index; m = 0, ..., N s -1, indicating a slow time dimension index; r and v are the distance and speed of the target relative to the radar; α is the target scattering coefficient; τ = 2r / c represents the target delay; f d =2vf c / c represents the Doppler frequency; c is the speed of light.

[0024] In an optional implementation, the discrete echo signal is subjected to discrete Fourier transform and matrix division to obtain a radar channel matrix containing target distance and speed information, including:

[0025] Perform discrete Fourier transform on the discrete echo signal along the fast time dimension to obtain the frequency domain signal of each subcarrier, and perform matrix division to obtain the radar channel matrix containing the target distance and speed information;

[0026] The expression of the radar channel matrix is:

[0027]

[0028] Where n = 0, ..., N c -1, indicating the frequency dimension index.

[0029] In an optional implementation, performing an inverse discrete Fourier transform on the radar channel matrix to obtain a range image includes:

[0030] Performing inverse discrete Fourier transform on the radar channel matrix along the frequency dimension to obtain a range image;

[0031] The expression of the distance image is:

[0032]

[0033] In an optional implementation, performing a discrete Fourier transform on the range image to obtain a range-velocity image includes:

[0034] Performing discrete Fourier transform on the range image along the slow time dimension to obtain a range-velocity image;

[0035] The expression of the distance-velocity image is:

[0036]

[0037] In an optional implementation, a peak value detection is performed on V to obtain a speed estimation result as follows:

[0038]

[0039] In the formula,

[0040] Estimated results based on speed It can be found that there are multiple peaks for the same target on the range-velocity image. The number of peaks is equal to the number of transmitting antennas. These peaks have the same distance and different speeds. By searching for the speed index difference between adjacent peaks of the target on the range-velocity image, the speed ambiguity number is determined, thereby solving the speed ambiguity problem.

[0041] The velocity deambiguation method for DDM MIMO-OFDM radar provided by the present invention has the following advantages.

[0042] The speed deambiguation method of the DDM MIMO-OFDM radar of the present invention is applied to the DDM MIMO-OFDM radar, which includes a plurality of transmitting antennas and receiving antennas. First, on the basis of the traditional Doppler multiplexing phase, an additional offset phase is applied to the transmitting antenna, and a radar orthogonal transmitting signal is constructed based on the phase design. Then, a target echo signal is constructed according to the transmitting signal, and the echo signal is preprocessed. The preprocessed echo signal is discrete Fourier transformed along the fast time dimension, and matrix division is performed to obtain a radar channel matrix containing target distance and speed information. The radar channel matrix is ​​subjected to frequency-dimensional inverse discrete Fourier transform and slow-time-dimensional discrete Fourier transform to obtain a distance-speed image. Peak detection is performed on the distance-speed image to obtain a speed estimation result. According to the speed estimation result, it can be obtained that there are multiple peaks on the same target on the distance-speed image, the number of peaks is equal to the number of transmitting antennas, and these peaks have the same distance and different speeds. By searching the speed index difference of adjacent peaks of the target on the distance-speed image, the speed ambiguity number is determined, thereby solving the speed ambiguity problem. By adding a small offset phase to some transmitting antennas, the equidistant distribution characteristics of the range-speed image target peaks in the speed dimension are broken, and the speed ambiguity number is determined by searching the speed index difference of adjacent peaks of the range-speed image target. Compared with the existing empty band speed deambiguation method, the present invention can estimate the true speed of the target and effectively solve the problem of target overlap.

[0043] In a second aspect, the present invention provides a speed deambiguation device for a DDM MIMO-OFDM radar, wherein the DDM MIMO-OFDM radar includes a plurality of transmitting antennas and receiving antennas, and the device includes:

[0044] A transmission signal construction module is used to construct a radar orthogonal transmission signal according to a preset Doppler multiplexing phase;

[0045] An echo signal acquisition module, used to construct a target echo signal based on the transmission signal, and pre-process the target echo signal to obtain a discrete echo signal corresponding to a single receiving antenna;

[0046] A channel matrix calculation module, used for performing discrete Fourier transform and matrix division on the discrete echo signal to obtain a radar channel matrix containing target distance and speed information;

[0047] A range-velocity profile calculation module is used to perform a range-dimensional inverse discrete Fourier transform and a velocity-dimensional discrete Fourier transform on the radar channel matrix to obtain a target range-velocity profile;

[0048] The speed fuzzy solution calculation module is used to perform peak detection on the target range-speed image, obtain several peaks of the same target on the target range-speed image, obtain speed index differences of adjacent peaks based on the peaks, and determine the speed fuzzy number based on the speed index differences.

[0049] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to execute the velocity deambiguation method of the DDM MIMO-OFDM radar of the first aspect or any corresponding embodiment thereof.

[0050] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the velocity deambiguation method for a DDM MIMO-OFDM radar according to the first aspect or any corresponding embodiment thereof.

[0051] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, wherein the computer instructions are used to enable a computer to execute the velocity deambiguation method for a DDM MIMO-OFDM radar according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] Figure 1The present invention provides a method flow chart of a velocity deambiguation method for a DDM MIMO-OFDM radar.

[0054] Figure 2 The present invention is a flow chart of a velocity deambiguation method for a DDM MIMO-OFDM radar according to an exemplary embodiment.

[0055] Figure 3 It is a schematic diagram of a radar time-frequency structure with four transmitting antennas according to an exemplary embodiment.

[0056] Figure 4 FIG. 4 is a schematic diagram of a single target distance-speed of a traditional DDM according to an exemplary embodiment.

[0057] Figure 5 FIG. 4 is a schematic diagram of single target distance-speed of PO-DDM according to an exemplary embodiment.

[0058] Figure 6 2 is a schematic diagram of distance-speed of two targets according to an empty belt method according to an exemplary embodiment.

[0059] Figure 7 is a schematic diagram of two target distances-speeds according to a PO-DDM method according to an exemplary embodiment.

[0060] Figure 8 It is a structural schematic diagram of a velocity deambiguation device for a DDM MIMO-OFDM radar provided in an embodiment of the present application.

[0061] Fig. 9 It is a structural schematic diagram of a computer device provided by an optional embodiment of the present invention. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0063] It should be understood that the "indication" mentioned in the embodiments of the present application can be a direct indication, an indirect indication, or an indication of an association relationship. For example, A indicates B, which can mean that A directly indicates B, for example, B can be obtained through A; it can also mean that A indirectly indicates B, for example, A indicates C, and B can be obtained through C; it can also mean that there is an association relationship between A and B.

[0064] In the description of the embodiments of the present application, the term "corresponding" may indicate a direct or indirect correspondence between two items, or an association relationship between the two items, or a relationship between indication and being indicated, configuration and being configured, and the like.

[0065] In an embodiment of the present application, "predefinition" can be achieved by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in a device (for example, including a terminal device and a network device). The present application does not limit its specific implementation method.

[0066] Multiple-input multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM) radar constructs virtual array elements through orthogonal waveforms, which can achieve higher angular resolution with a limited number of antennas. Orthogonal frequency division multiplexing (OFDM) is a multi-carrier transmission technology commonly used in modern communications. It has the advantages of large time-bandwidth product, flexible parameter design, and good anti-interception performance. Combining OFDM with MIMO radar can achieve high-resolution ranging and high-precision angle measurement, and has received widespread attention in automotive millimeter-wave radars in recent years.

[0067] Multiple-input multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM) radar uses the Doppler-Division Multiplexing (DDM) method to separate the target echoes from different transmitting antennas in the Doppler domain (velocity domain) by adding different phases between adjacent OFDM symbols of different transmitting antennas. However, the DDM method reduces the maximum unambiguous speed and produces a speed ambiguity problem. To address the DDM speed ambiguity problem, the existing method is to insert an empty band on the speed spectrum and change the traditional DDM phase. This method divides the target speed spectrum into multiple sub-bands and estimates the true speed of the target through coherent or non-coherent accumulation of multiple sub-bands. However, when multiple targets are at the same distance and the speed difference is an integer multiple of the maximum unambiguous speed, this empty band speed deambiguation method will have a target overlap problem.

[0068] Therefore, an embodiment of the present invention provides a speed deambiguation method for a DDM MIMO-OFDM radar, which breaks the equidistant distribution characteristics of the range-speed image target peaks in the speed dimension by adding a small offset phase to some transmitting antennas, and determines the speed ambiguity number by searching the speed index difference of adjacent peaks of the range-speed image target. Compared with the existing empty band speed deambiguation method, the present invention can estimate the true speed of the target and effectively solve the problem of target overlap.

[0069] A velocity deambiguation method for a DDM MIMO-OFDM radar according to an embodiment of the present invention includes a plurality of transmitting antennas and a receiving antenna. The process of the method is as follows: Figure 1 As shown, the following steps are included.

[0070] S101. Construct a radar orthogonal transmission signal according to a preset Doppler multiplexing phase.

[0071] Optionally, in step S101, the number of DDM MIMO-OFDM radar transmitting antennas is set to N. Tx , the number of receiving array elements is 1, the number of OFDM symbols and the number of subcarrier frequencies are N s and N c . The first step is to design the DDM phase. Traditional DDM adds linear equally spaced phases between adjacent OFDM symbols of different transmitting antennas. The DDM phase proposed in this embodiment is based on the traditional DDM phase, and a small offset phase is additionally applied to some transmitting antennas. This method is called PO-DDM (Phase Offset Doppler-Division Multiplexing). Therefore, the phase of the kth transmitting antenna can be expressed as:

[0072]

[0073] Where k represents the kth transmitting antenna, and are the Doppler multiplexing phase and the added offset phase of the kth transmitting antenna respectively;

[0074] The expression of the transmitted signal is:

[0075]

[0076] Where N s and N c are the number of OFDM symbols and subcarrier frequencies respectively; S(n,m) is the communication information carried by the nth subcarrier frequency on the mth OFDM symbol; T s =T+T g is a complete OFDM symbol period; T = 1 / Δf is the effective OFDM symbol period; Δf is the subcarrier frequency interval; T g is the cyclic prefix period; rect(t / T s ) is a rectangular window function, when 0 <t<T s 1 when , otherwise 0; f c For the carrier frequency.

[0077] S102: construct a target echo signal based on the transmission signal, and preprocess the echo signal to obtain discrete echo signals corresponding to each receiving antenna.

[0078] Optionally, in step S102, a target echo model is constructed according to the constructed transmission signal. The distance and speed of the target relative to the radar are set to r and v respectively, and the target scattering coefficient is α. Then τ = 2r / c and f d =2vf c / c represent the target delay and Doppler frequency respectively, and c is the speed of light. After the signals from different transmitting antennas are transmitted by the target, the echoes received by a single receiving antenna are pre-processed, including down-conversion, sampling, and cyclic prefix removal, to obtain:

[0079]

[0080] Where i = 0,…,N c -1, indicating fast time dimension index; m = 0, ..., N s -1, indicating a slow time dimension index; r and v are the distance and speed of the target relative to the radar; α is the target scattering coefficient; τ = 2r / c represents the target delay; f d =2vf c / c represents the Doppler frequency; c is the speed of light.

[0081] S103: Perform discrete Fourier transform and matrix division on the discrete echo signal to obtain a radar channel matrix containing target distance and speed information.

[0082] Specifically, in step S103, a discrete Fourier transform is performed on the discrete echo signal along the fast time dimension to obtain a frequency domain signal of each subcarrier, and matrix division is performed to obtain a radar channel matrix containing target distance and speed information.

[0083] Optionally, in the above steps, DFT is performed on y(i,m) with respect to i (fast time dimension) to obtain the frequency domain signal of each subcarrier. Matrix division eliminates the influence of the modulation symbol matrix on radar performance and obtains the radar channel matrix containing target distance and speed information:

[0084]

[0085] Where n = 0, ..., N c -1, indicating the frequency dimension index.

[0086] S104, performing a distance-dimensional inverse discrete Fourier transform and a velocity-dimensional discrete Fourier transform on the radar channel matrix to obtain a target range-velocity image.

[0087] Specifically, in step S104, an inverse discrete Fourier transform is performed on the radar channel matrix along the frequency dimension to obtain a range image; and a discrete Fourier transform is performed on the range image along the slow time dimension to obtain a target range-speed image.

[0088] Optionally, in the above steps, an inverse discrete Fourier transform (IDFT) is performed on D(n,m) with respect to n (frequency dimension) to obtain a range image:

[0089]

[0090] Perform DFT on R(p,m) with respect to m (slow time dimension) to obtain the distance-velocity image:

[0091]

[0092] S105, performing peak detection on the target range-speed image to obtain a plurality of peaks of the same target, and obtaining speed index differences of adjacent peaks based on the peaks; and determining a speed fuzzy number based on the speed index differences.

[0093] Optionally, in step S105, peak detection is performed on the range-velocity image V, and the velocity estimation result is:

[0094]

[0095] In the formula,

[0096] According to the velocity estimation results, we can get N Tx peaks with the same distance and different speeds. Moreover, the DDM phase This causes the target peak corresponding to the kth transmitting antenna to move in the velocity dimension. The velocity ambiguity number is determined by searching for the velocity index difference of adjacent peaks of the range-velocity image target.

[0097] In summary, the speed deambiguation method of the DDM MIMO-OFDM radar provided in the embodiment of the present invention is applied to the DDM MIMO-OFDM radar, which includes a plurality of transmitting antennas and receiving antennas. First, on the basis of the traditional Doppler multiplexing phase, an additional offset phase is applied to the transmitting antenna, and a radar orthogonal transmitting signal is constructed based on the phase design. Then, a target echo signal is constructed according to the transmitting signal, and the echo signal is preprocessed. The preprocessed echo signal is discrete Fourier transformed along the fast time dimension, and matrix division is performed to obtain a radar channel matrix containing target distance and speed information. The radar channel matrix is ​​inversely discrete Fourier transformed along the frequency dimension to obtain a range image; the range image is discrete Fourier transformed along the slow time dimension to obtain a range-speed image. The range-speed image is peak detected to obtain a speed estimation result. According to the speed estimation result, it can be obtained that there are multiple peaks on the same target on the range-speed image, and the number of peaks is equal to the number of transmitting antennas, and these peaks have the same distance and different speeds. By searching for the speed index difference of the adjacent peaks of the target on the range-speed image, the speed ambiguity number is determined, thereby solving the speed ambiguity problem. By adding a small offset phase to some transmitting antennas, the equidistant distribution characteristics of the target peaks of the range-speed image in the speed dimension are broken, and the speed ambiguity number is determined by searching for the speed index difference of the adjacent peaks of the target on the range-speed image. Compared with the existing empty band speed deambiguation method, the present invention can estimate the true speed of the target and effectively solve the problem of target overlap.

[0098] In order to facilitate understanding of the velocity deambiguation method for DDM MIMO-OFDM radar provided in the above embodiment, an example will be used for specific description below. The method flow of this example is as follows: Figure 2 As shown, the method flow is the same as that provided in the above embodiment and will not be repeated here.

[0099] In this example, the number of transmitting antennas N Tx =4 for example, Figure 3 As shown in Figure 2, this method is not limited by the number of transmitting antennas and can be extended to any number of transmitting antennas. The traditional DDM phase sequence is set to The additional phase sequence is set to This means that an additional offset phase is added to Tx1 and Tx2.

[0100] First, consider the first case, when the target speed is less than the maximum unambiguous speed. After the above processing, the speed index difference of adjacent peaks of the same target is expressed as Δ 01 , Δ 12 , Δ 23 and Δ 30The velocity index difference of adjacent target peaks corresponding to the traditional DDM is the same, with Δ 01 =Δ 12 =Δ 23 =Δ 30 =N s / 4. However, for PO-DDM, the velocity index difference of adjacent peaks is different, at this time:

[0101]

[0102] In the formula,

[0103] Next, consider the second case, when the target true speed is greater than the maximum unambiguous speed. Then the target true speed v can be expressed as:

[0104] v=v est +ξV max ,ξ=1,2,3;

[0105] In the formula, v est is the estimated speed of the target in the range-speed image, ξ is the speed fuzzy number, V max =c / (2f c T s N Tx ) is the maximum unambiguous velocity of the DDM MIMO-OFDM radar. Note that the essence of the DDM velocity deambiguation problem is to determine the ambiguity number k.

[0106] When ξ≠0, the velocity index difference of the target peak value generated by the MIMO-OFDM radar using traditional DDM is the same, and there is Δ 01 =Δ 12 =Δ 23 =Δ 30 =N s / 4, which makes it difficult to determine ξ. However, the speed index difference of adjacent peaks of the target corresponding to PO-DDM is different under different fuzzy numbers, and the results are shown in Table 1. The speed index difference of adjacent peaks under different fuzzy numbers. It can be seen that the speed index difference of adjacent peaks under different fuzzy numbers is cyclically shifted. Therefore, the fuzzy number ξ can be obtained by looking up the speed index difference of adjacent peaks. In addition, in order to correctly associate these peaks with the corresponding targets, the peaks of the same target have the same distance, and the speed index difference of adjacent peaks should conform to a certain pattern in Table 1.

[0107] Table 1

[0108]

[0109] In order to better illustrate the technical effect achieved by the velocity deambiguation method of the DDM MIMO-OFDM radar provided in this embodiment, the method of the present invention is compared with the existing method by simulation experiment, wherein the radar parameter settings are shown in Table 2. According to the parameter settings in Table 2, the maximum unambiguous speed of the radar is 37.08 m / s. Then the distance-speed diagrams of Tx1 and Tx2 are shifted left by 6 and right by 10 speed units in the speed dimension, respectively.

[0110] Table 2

[0111]

[0112] The simulation results are as follows: Figure 4 and Figure 5 It is the single target range-velocity image corresponding to the traditional DDM and PO-DDM methods. Figure 4 For traditional DDM; Figure 5 is PO-DDM. The distance of a single target is 50m and the speed is 45m / s. Figure 4 and Figure 5 It can be obtained that the velocity index difference of adjacent peaks of the range-velocity image corresponding to the traditional DDM is the same and is 64. The velocity index difference of adjacent peaks corresponding to the PO-DDM is Δ 01 , Δ 12 and Δ 23 They are 64, 58 and 80 respectively. Combining Table 1, we can see that the fuzzy number is ξ=1, the target true speed is 45.19m / s, and the speed estimation error is 0.19m / s.

[0113] Figure 6 and Figure 7 These are the two target range-velocity images corresponding to the existing empty band method and PO-DDM method. Figure 6 It is empty with method; Figure 7 The two targets are at the same distance and the speed difference is approximately equal to an integer multiple of the maximum unambiguous speed. The distance of target 1 is 50m and the speed is 6m / s. The distance of target 2 is 50m and the speed is 80m / s. The number of empty bands inserted in the empty band method is 2, so the target range-speed image is divided into 6 sub-bands at equal intervals in the speed dimension, and the maximum unambiguous speed is 24.72m / s.

[0114] Depend on Figure 6 and Figure 7It can be seen that the range-velocity image generated by the empty band method can detect 6 peaks, which means that the targets overlap and the two targets cannot be correctly identified because the intervals between adjacent peaks are equal. The PO-DDM method can detect 8 peaks. In order to correctly associate these peaks with the corresponding targets, the velocity index difference of adjacent peaks should conform to a pattern in Table 1. After peak detection and association, the velocity index difference Δ of adjacent peaks of target 1 and target 2 is obtained. 01 , Δ 12 , Δ 23 and Δ 30 They are {58, 80, 54, 64} and {54, 64, 58, 80} respectively. Combined with Table 1, we can see that the fuzzy numbers of targets 1 and 2 are ξ=0 and ξ=2 respectively, and then the speeds of targets 1 and 2 are 6.12m / s and 80.13m / s respectively, which are 0.12m / s and 0.13m / s different from the actual speeds.

[0115] In summary, the speed deambiguation method of the DDM MIMO-OFDM radar provided in this example determines the speed ambiguity number by searching the speed index difference of the adjacent peaks of the target on the range-speed image, thereby solving the speed ambiguity problem. By adding a small offset phase to some transmitting antennas, the equidistant distribution characteristics of the target peaks of the range-speed image in the speed dimension are broken, and the speed ambiguity number is determined by searching the speed index difference of the adjacent peaks of the target in the range-speed image. Compared with the existing empty band speed deambiguation method, the present invention can estimate the true speed of the target and effectively solve the problem of target overlap.

[0116] In the embodiments of the present application, a speed deambiguation device for a DDM MIMO-OFDM radar is also provided, which is used to implement the above embodiments and preferred implementation modes, and will not be repeated hereafter. As used below, the term "module" may be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0117] The embodiment of the present application provides a speed deambiguation device for a DDM MIMO-OFDM radar. Figure 8 1 is a schematic diagram of a speed deambiguation device of a DDM MIMO-OFDM radar provided in an embodiment of the present application. The DDM MIMO-OFDM radar includes a plurality of transmitting antennas and receiving antennas. The device includes:

[0118] The transmission signal construction module 801 is used to construct a radar orthogonal transmission signal according to a preset Doppler multiplexing phase;

[0119] The echo signal acquisition module 802 is used to construct a target echo signal based on the transmission signal, and pre-process the target echo signal to obtain a discrete echo signal corresponding to a single receiving antenna;

[0120] A channel matrix calculation module 803 is used to perform discrete Fourier transform and matrix division on the discrete echo signal to obtain a radar channel matrix containing target distance and speed information;

[0121] The range-velocity profile calculation module 804 is used to perform a range-dimensional inverse discrete Fourier transform and a velocity-dimensional discrete Fourier transform on the radar channel matrix to obtain a target range-velocity profile;

[0122] The speed ambiguity solution calculation module 805 is used to perform peak detection on the target range-speed image to obtain several peaks of the same target, obtain speed index differences of adjacent peaks based on the peaks, and determine the speed ambiguity number based on the speed index differences.

[0123] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0124] The velocity deambiguation device of the DDM MIMO-OFDM radar in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0125] The embodiment of the present invention also provides a computer device having the above Figure 8 The velocity deambiguation device of the DDM MIMO-OFDM radar is shown.

[0126] See also Fig. 9 , Fig. 9 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Fig. 9As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display graphic information in a graphical user interface on an external input / output device (such as a display device coupled to an interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig. 9 A processor 10 is taken as an example.

[0127] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0128] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0129] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0130] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0131] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Fig. 9 The example of connecting through bus is taken in the following.

[0132] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0133] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0134] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A velocity deambiguation method for DDM MIMO-OFDM radar, characterized in that: The DDM MIMO-OFDM radar includes a plurality of transmitting antennas and receiving antennas, and the method includes: Constructing radar orthogonal transmission signals according to the preset Doppler multiplexing phase; Based on the transmission signal, a target echo signal is constructed, and the target echo signal is preprocessed to obtain a discrete echo signal corresponding to a single receiving antenna; Performing discrete Fourier transform and matrix division on the discrete echo signal to obtain a radar channel matrix containing target distance and speed information; Performing a distance-dimensional inverse discrete Fourier transform and a velocity-dimensional discrete Fourier transform on the radar channel matrix to obtain a target range-velocity image; Peak detection is performed on the target range-speed image to obtain a plurality of peaks of the same target, and based on the peaks, velocity index differences of adjacent peaks are obtained, and based on the velocity index differences, a velocity fuzzy number is determined.

2. The method according to claim 1, characterized in that The step of constructing a radar orthogonal transmission signal according to a preset Doppler multiplexing phase comprises: Adding an offset phase to the traditional Doppler multiplexing phase to obtain the phase of each transmitting antenna; Based on the phase, construct a transmission signal of each transmitting antenna; Wherein, the expression of the phase of each transmitting antenna is: Where k represents the kth transmitting antenna, and are the Doppler multiplexing phase and the added offset phase of the kth transmitting antenna respectively; The expression of the transmission signal is: Where N s and N c are the number of OFDM symbols and subcarrier frequencies respectively; S(n,m) is the communication information carried by the nth subcarrier frequency on the mth OFDM symbol; T s =T+T g is a complete OFDM symbol period; T = 1 / Δf is the effective OFDM symbol period; Δf is the subcarrier frequency interval; T g is the cyclic prefix period; rect(t / T s ) is a rectangular window function, when 0 <t<T s 1 when , otherwise 0; f c For the carrier frequency.

3. The method according to claim 2, characterized in that The expression of the discrete echo signal is: Where i = 0,…,N c -1, indicating fast time dimension index; m = 0, ..., N s -1, indicating a slow time dimension index; r and v are the distance and speed of the target relative to the radar, respectively; α is the target scattering coefficient; τ = 2r / c represents the target delay; f d =2vf c / c represents the Doppler frequency; c is the speed of light.

4. The method according to claim 3, characterized in that The discrete Fourier transform and matrix division are performed on the discrete echo signal to obtain a radar channel matrix containing target distance and speed information, including: Performing discrete Fourier transform on the discrete echo signal along the fast time dimension to obtain a frequency domain signal of each subcarrier, and performing matrix division to obtain a radar channel matrix containing target distance and speed information; The expression of the radar channel matrix is: Where n = 0, ..., N c -1, indicating the frequency dimension index.

5. The method according to claim 4, characterized in that The performing a range-dimensional inverse discrete Fourier transform on the radar channel matrix to obtain a range image includes: Performing an inverse discrete Fourier transform on the radar channel matrix along the frequency dimension to obtain a range image; The expression of the range image is: p=0,L,N c -1。 6. The method according to claim 5, characterized in that The performing of a velocity-dimensional discrete Fourier transform on the range image to obtain a range-velocity image comprises: Performing discrete Fourier transform on the range image along the slow time dimension to obtain a range-velocity image; The expression of the distance-velocity image is: q=0,L,N s -1。 7. The method according to claim 6, characterized in that The peak value detection of the target range-velocity profile includes: Performing peak detection on the target range-velocity image to obtain a velocity estimation result; The expression of the speed estimation result is: In the formula, 8. A velocity deambiguation device for a DDM MIMO-OFDM radar, characterized in that: The DDM MIMO-OFDM radar includes a plurality of transmitting antennas and receiving antennas, and the device includes: A transmission signal construction module is used to construct a radar orthogonal transmission signal according to a preset Doppler multiplexing phase; An echo signal acquisition module, used to construct a target echo signal based on the transmission signal, and pre-process the target echo signal to obtain a discrete echo signal corresponding to a single receiving antenna; A channel matrix calculation module, used for performing discrete Fourier transform and matrix division on the discrete echo signal to obtain a radar channel matrix containing target distance and speed information; A range-velocity profile calculation module is used to perform a range-dimensional inverse discrete Fourier transform and a velocity-dimensional discrete Fourier transform on the radar channel matrix to obtain a target range-velocity profile; The speed fuzzy solution calculation module is used to perform peak detection on the target range-speed image, obtain several peaks of the same target on the target range-speed image, obtain speed index differences of adjacent peaks based on the peaks, and determine the speed fuzzy number based on the speed index differences.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the velocity deambiguation method of the DDM MIMO-OFDM radar according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the velocity deambiguation method of the DDM MIMO-OFDM radar according to any one of claims 1 to 7.

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