Non-ambiguity estimation method for co-location MR-FDA-MIMO radar system

Abstract

The invention provides a non-fuzzy estimation method for a co-location MR-FDA-MIMO radar system, and the method comprises the steps: determining an array element position coefficient according to the number of array elements of a receiving and transmitting array, so as to configure the receiving and transmitting array of a radar system; transmitting an orthogonal frequency modulation signal; in response to the echo signal, determining system snapshot data and a covariance matrix and a priori principal value distance thereof; according to the covariance matrix, determining an equivalent uniform linear FDA-MIMO radar and a differential single snapshot signal thereof; performing main value distance compensation on the single snapshot signal according to the priori main value distance; removing the signal correlation of the compensated data, and determining a covariance matrix of the single snapshot signal based on a removal result; based on a covariance matrix of a single snapshot signal, a target angle, a distance fuzzy number, a main value distance difference and a target distance are estimated, when the number of array elements is fixed, the method fully utilizes equivalent uniform linear radar extension to obtain a virtual array aperture, the limitation of the number of the array elements is broken, and the estimation precision is improved.

Description

Technical Field

[0001] The present invention relates to the field of radar technology, and in particular to an unambiguous estimation method for a co-site MR-FDA-MIMO radar system. Background Art

[0002] With the increasing complexity of electromagnetic and geographical environments, traditional phased array radars can no longer meet current needs. FDA breaks through the scanning method of traditional phased arrays and introduces a transmission frequency offset that is much smaller than the operating frequency between the transmitting antenna units, which can form a time-varying transmission pattern that depends on distance-angle in space, thereby realizing two-dimensional matched filtering of distance angle. In order to extract the distance information in the transmission spatial frequency, Xu et al. combined the FDA radar with the multiple-input multiple-output technology and proposed a new FDA-MIMO radar, which not only realizes the joint estimation of distance-angle, but also retains the full-domain coverage characteristics of the MIMO radar.

[0003] The existing FDA-MIMO radar achieves the joint estimation of target distance and angle, but the target source estimation and target estimation accuracy are still limited by the number of array elements. In practical applications, in order to meet the accuracy requirements, a large number of antennas need to be equipped, which is too expensive for the hardware. At the same time, there is also the phenomenon of mutual coupling of array elements, which causes the loss of target estimation accuracy. The current FDA-MIMO radar that combines nested arrays and coprime arrays has broken through the limitation of the number of array elements and improved the target estimation accuracy to a certain extent, but the virtual aperture of the array is not fully utilized, and the estimation accuracy can be further improved. In addition, the range ambiguity problem is not considered. When the target range is ambiguous, the estimation performance decreases or even fails. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, the present invention provides an unambiguous estimation method for a co-sited MR-FDA-MIMO radar system, which specifically includes:

[0005] In a first aspect, the present invention provides an unambiguous estimation method for a co-sited MR-FDA-MIMO radar system, comprising:

[0006] Determine the array element position coefficients corresponding to the transmitting array and the receiving array according to the number of array elements of the transmitting array and the receiving array respectively, and configure the transmitting array and the receiving array of the co-sited MR-FDA-MIMO radar system according to the corresponding array element position coefficients;

[0007] Controlling the transmitting array of the co-sited MR-FDA-MIMO radar system to transmit orthogonal frequency modulation signals;

[0008] In response to the echo signal received by the receiving array, the snapshot data of the co-sited MR-FDA-MIMO radar system, the covariance matrix of the snapshot data of the co-sited MR-FDA-MIMO radar system and the prior principal value distance are determined; according to the covariance matrix, the equivalent uniform linear FDA-MIMO radar and the differential single snapshot signal of the equivalent uniform linear FDA-MIMO radar are determined; according to the prior principal value distance, the single snapshot signal is compensated for the principal value distance to obtain the compensated data; the signal correlation of the compensated data is removed by using a two-dimensional spatial smoothing technology, and the covariance matrix of the single snapshot signal is determined based on the removal result; based on the covariance matrix of the single snapshot signal, the MUSIC algorithm is used to estimate the target angle and distance ambiguity number, as well as the principal value distance difference and the target distance.

[0009] In a second aspect, the present invention further provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0010] Memory, used to store computer programs;

[0011] The processor is used to implement any method provided in the first aspect when executing a program stored in the memory.

[0012] In a third aspect, the present invention provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, any one of the methods provided in the first aspect is implemented.

[0013] Beneficial effects of the present invention:

[0014] The unambiguous estimation method of the co-sited MR-FDA-MIMO radar system provided by the present invention determines the array element position coefficients corresponding to the transmitting array and the receiving array according to the number of array elements of the transmitting array and the receiving array respectively, and configures the transmitting array and the receiving array of the co-sited MR-FDA-MIMO radar system according to the corresponding array element position coefficients; controls the transmitting array of the co-sited MR-FDA-MIMO radar system to transmit an orthogonal frequency modulation signal; determines the snapshot data of the co-sited MR-FDA-MIMO radar system, the covariance matrix of the snapshot data of the co-sited MR-FDA-MIMO radar system and the priori principal value distance in response to the echo signal received by the receiving array; determines the equivalent uniform linear FDA- MIMO radar, and the differential single snapshot signal of the equivalent uniform linear FDA-MIMO radar; according to the prior principal value distance, the principal value distance compensation is performed on the single snapshot signal to obtain the compensated data; the signal correlation of the compensated data is removed by using the two-dimensional spatial smoothing technology, and the covariance matrix of the single snapshot signal is determined based on the removal result; based on the covariance matrix of the single snapshot signal, the MUSIC algorithm is used to estimate the target angle and range ambiguity number, as well as the principal value distance difference and the target distance. When the number of array elements is constant, the determined equivalent uniform linear FDA-MIMO radar is fully utilized to expand the virtual array aperture. While solving the target distance ambiguity problem, the limitation of the number of array elements on the estimated number is broken, and the target distance angle estimation accuracy is further improved.

[0015] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of a flow chart of an unambiguous estimation method for a co-sited MR-FDA-MIMO radar system provided by the present invention;

[0017] Figure 2 A schematic diagram of a transceiver array configuration method of a co-sited MR-FDA-MIMO radar system provided by the present invention;

[0018] Figure 3 A schematic diagram of the principle of a two-dimensional space smoothing technology provided by the present invention;

[0019] Figure 4 A schematic diagram of simulation data provided by the present invention;

[0020] Figure 5 Another schematic diagram of simulation data provided by the present invention;

[0021] Figure 6 A schematic diagram of another simulation data provided by the present invention;

[0022] Figure 7A schematic diagram of another simulation data provided by the present invention;

[0023] Figure 8 A schematic diagram of another simulation data provided by the present invention;

[0024] Fig. 9 The present invention provides another simulation data schematic diagram. DETAILED DESCRIPTION

[0025] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0026] Figure 1 A flow chart of an MR-FDA-MIMO radar unambiguous estimation method provided by the present invention is shown in FIG. Figure 1 As shown, the method includes:

[0027] S101, determining the array element position coefficients corresponding to the transmitting array and the receiving array according to the number of array elements of the transmitting array and the receiving array respectively, and configuring the transmitting array and the receiving array of the co-sited MR-FDA-MIMO radar system according to the corresponding array element position coefficients.

[0028] Optionally, the number of array elements and the configuration method of the transmitting array and the receiving array are the same.

[0029] MR stands for minimum redundancy, FDA stands for frequency diversity array, and MIMO stands for multiple input multiple output. The co-sited MR-FDA-MIMO radar system is to configure the current FDA-MIMO radar's transceiver array into a minimum redundancy array.

[0030] Sparse arrays break through the limitation of array element size on array freedom through non-uniform array configuration, and can achieve target parameter estimation when the number of signal sources is greater than the actual number of array elements. Sparse arrays mainly include nested arrays, coprime arrays and minimum redundancy arrays (MRA).

[0031] Exemplary, MR-FDA-MIMO radar, according to Figure 2 The transmit and receive array is configured as shown, D m The value of can be derived from the number of array elements. Optionally, the MR-FDA-MIMO radar array configuration parameters are shown in Table 1.

[0032] Table 1 MR-FDA-MIMO radar array configuration

[0033] Number of array elements Location coefficient 4 0 1 4 6 5 0 1 4 7 9 6 0 1 2 6 10 13 7 0 1 2 6 10 14 17 8 0 1 2 11 15 18 21 23 9 0 1 2 14 18 21 24 27 29 10 0 1 4 10 16 22 28 30 33 35

[0034] It can be seen that the structure of the co-sited MR-FDA-MIMO radar system transceiver array of the present invention is a sparse array. Through the sparse configuration of the array antenna, the bandwidth and array aperture can be equivalently improved, the system spatial resolution and parameter estimation performance can be significantly improved, and the hardware cost can be reduced in practical applications.

[0035] S102 . Control the transmitting array of the co-sited MR-FDA-MIMO radar system to transmit an orthogonal frequency modulation signal.

[0036] In a possible implementation, the signal carrier frequency of the transmitting array element is expressed as:

[0037] f m =f0+D m Δf,

[0038] Among them, f m represents the signal carrier frequency of the mth transmitting array element, f0 represents the frequency on the reference array element, Δf represents the frequency deviation of the array element, and D m Represents the array element position coefficient, m=1,2,…,M, and m represents the index of the transmitting array element.

[0039] S103, in response to the echo signal received by the receiving array, determine the snapshot data of the co-sited MR-FDA-MIMO radar system, the covariance matrix of the snapshot data of the co-sited MR-FDA-MIMO radar system, and the prior principal value distance; determine the equivalent uniform linear FDA-MIMO radar and the differential single snapshot signal of the equivalent uniform linear FDA-MIMO radar according to the covariance matrix; perform principal value distance compensation on the single snapshot signal according to the prior principal value distance to obtain compensated data; use two-dimensional spatial smoothing technology to remove signal correlation of the compensated data, and determine the covariance matrix of the single snapshot signal based on the removal result; based on the covariance matrix of the single snapshot signal, use the MUSIC algorithm to estimate the target angle and distance ambiguity number, as well as the principal value distance difference and the target distance.

[0040] Specifically, M transmitting array elements in the co-sited MR-FDA-MIMO radar system transmit mutually orthogonal frequency modulation signals, and matched filtering is performed on the echo signal received by each receiving array element at the receiving end.

[0041] Step S103 may be performed by a receiving end in the co-located MR-FDA-MIMO radar system.

[0042] In one possible implementation, a snapshot of the signal output data of a co-located MR-FDA-MIMO radar system is represented as:

[0043] y=y s +y n ,

[0044] Where y represents the snapshot data of the co-sited MR-FDA-MIMO radar system, y n represents the system noise, y s Indicates a snapshot of signal output data.

[0045] The following is a further detailed description of the process of determining the signal output data snapshot of the co-located MR-FDA-MIMO radar system:

[0046] Based on the signal carrier frequency of the transmitting array element in step S102 and the configuration result of the transceiver array of the co-located MR-FDA-MIMO radar system, the signal transmitted on the mth array element can be further obtained, which is expressed as:

[0047]

[0048] Among them, s m (t) represents the signal transmitted from the mth array element, M represents the total number of array elements, t represents the time variable, T p represents the pulse width, e represents the natural logarithm, j represents the imaginary unit, and f m represents the signal carrier frequency of the mth transmitting array element, E represents the total power of the transmitted signal, represents the power-normalized baseband envelope of the mth transmitted signal.

[0049] The baseband envelopes of each transmitting array element satisfy the orthogonal condition:

[0050]

[0051] Where τ is the delay, (·) * represents the conjugation operation.

[0052] For a far-field point target located at a distance of r and an angle of θ, the echo signal received by the nth array element at the receiving end is expressed as:

[0053]

[0054] Among them, β represents the complex scattering coefficient of the target, τ m,n represents the propagation delay of the signal transmitted by the mth array element and received by the nth array element, which can be expressed as:

[0055]

[0056] Where c represents the propagation speed of electromagnetic waves, and d is the array element spacing, which is set to half of the wavelength λ0 corresponding to the reference array element carrier frequency.

[0057] Under the narrowband assumption, the mth matched filter output of the nth receiving array element is:

[0058]

[0059] in and Represent the transmit and receive spatial frequencies respectively.

[0060] Therefore, the signal output data snapshot can be expressed as:

[0061]

[0062] in, represents the Kronecker product, (·) T represents the transpose operation, b(θ) and a(r,θ) represent the receiving and transmitting steering vectors respectively, and the specific form is:

[0063]

[0064] Among them, a r (r) and a a (θ) represents the launch distance guidance vector and the launch time guidance vector respectively, and ⊙ represents the Hadamard product.

[0065] Considering the system noise y n , then the snapshot data of the MR-FDA-MIMO radar system can be expressed as:

[0066] y=y s +y n .

[0067] Furthermore, according to the covariance matrix, an equivalent uniform linear FDA-MIMO radar and a differential single snapshot signal of the equivalent uniform linear FDA-MIMO radar are determined, including: vectorizing the covariance matrix to obtain a vectorized covariance matrix; performing redundancy removal and rearrangement processing on the vectorized covariance matrix to obtain an equivalent uniform linear FDA-MIMO radar and a differential single snapshot signal of the equivalent uniform linear FDA-MIMO radar.

[0068] Optionally, a single snapshot signal is represented as:

[0069]

[0070] Where z represents a single snapshot signal, F represents a selection matrix, represents the vectorized covariance matrix, represents the target signal, a d (r,θ) represents the send-receive joint steering vector, r represents the target distance, θ represents the target angle, represents the noise signal power, i d Represents the identity matrix after vectorization, redundancy removal, and rearrangement.

[0071] Specifically, because the noise and target signal are independent of each other, the covariance matrix of the snapshot data y is:

[0072]

[0073] in, and represent the target signal and noise signal power respectively, represents the transmit-receive joint steering vector, I M represents an M×M-dimensional unit vector.

[0074] The covariance matrix R is vectorized to obtain the vectorized covariance matrix, which is expressed as:

[0075]

[0076] in, represents the equivalent steering vector, By the identity matrix I M Vectorization obtained.

[0077] Further, The redundancy removal and rearrangement processing is performed, specifically, by selecting the matrix F to delete the repeated elements in the equivalent steering vector, and reordering it into a uniform linear FDA-MIMO radar receiving data, that is, a single snapshot signal, which is expressed as:

[0078]

[0079] Among them, a d (r,θ) represents the transmit-receive joint steering vector of the equivalent uniform linear FDA-MIMO radar obtained by de-redundancy rearrangement, and its specific form is:

[0080]

[0081] Among them, the number of array elements of the equivalent uniform linear FDA-MIMO radar obtained by de-redundancy rearrangement is 2M d -1.

[0082] The present invention utilizes a minimum redundant array to expand the array aperture, which can expand the array aperture and solve the problem that the number of FDA-MIMO radar target estimates is limited by the number of array elements without increasing the system hardware cost; at the same time, when the number of array elements is less than the number of target estimates, unambiguous distance angle estimation is achieved, the target distance ambiguity problem is solved, and further, the array degree of freedom is expanded, effectively improving the estimation accuracy of the distance angle.

[0083] In a possible implementation, the compensated data is expressed as:

[0084]

[0085] Among them, z c represents the compensated data, z represents the single snapshot signal, g represents the compensation vector, represents the target signal, a d (Δr, p, θ) represents the compensated transmit-receive joint steering vector, Δr represents the principal value distance difference, p represents the target range ambiguity number, θ represents the target angle, represents the noise signal power, i d represents the identity matrix after vectorization, redundancy removal and rearrangement, and ⊙ represents the Hadamard product.

[0086] Specifically, under the condition of distance ambiguity, the target distance can be written as:

[0087] r=r0+(p-1)R u ,

[0088] Among them, r0 represents the target principal value distance, R u represents the maximum unambiguous distance of the radar system, and p represents the distance ambiguity number of the target.

[0089] After compensating for r0, p can be estimated directly to achieve unambiguous estimation of the target.

[0090] The compensation vector is:

[0091]

[0092] in, M represents all elements are 1 d dimensional vector, h(r b ) represents the transmit spatial frequency compensation vector, which is in the form of:

[0093]

[0094] Among them, r b It means that the principal value distance obtained after pulse compression deviates from the actual principal value distance. The principal value distance difference is defined as:

[0095] Δr=r a -r b ,

[0096] The data after compensation is:

[0097]

[0098] The present invention uses distance compensation to eliminate the influence of the main value distance, can realize the estimation of the distance fuzzy number, and can solve the distance fuzzy problem of the target. When the number of array elements is the same, the target distance angle estimation accuracy obtained by the present invention is higher and the algorithm estimation performance is better.

[0099] The compensation data is a single snapshot signal, and the traditional subspace-based super-resolution algorithm cannot be directly applied. Because the compensation data is distance-angle coupled, a two-dimensional spatial smoothing technique is used to obtain the data covariance matrix at the expense of a certain aperture.

[0100] The schematic diagram of the principle of two-dimensional space smoothing technology is as follows Figure 3 As shown, the equivalent uniform array is divided into M s There are overlapping sub-arrays, each with M elements. n , then the data transmitted by the i-th sub-array and received by the j-th sub-array is:

[0101] z ij =Γ ij z c ,

[0102] Among them, Γ ij Represents a two-dimensional selection matrix, which is in the form of:

[0103]

[0104] After spatial smoothing, the covariance matrix can be reconstructed as:

[0105]

[0106] In a possible implementation, the estimated value of the principal value distance difference is expressed as:

[0107]

[0108] in, represents the estimated value of the principal value distance, represents the subarray transmit-receive joint steering vector, Δr represents the principal value distance difference, represents the distance fuzzy number estimate, represents the target angle estimate, U n represents the noise subspace, and the superscript H represents the conjugate transpose operation.

[0109] In one possible implementation, the estimated value of the target distance is expressed as:

[0110]

[0111] in, represents the estimated value of the target distance, Represents the estimated value of the principal value distance, r b represents the a priori principal value distance obtained by pulse compression, Distance fuzzy number estimate, R u represents the maximum unambiguous number.

[0112] Specifically, the orthogonality of the signal subspace and the noise subspace is used to perform a two-dimensional spectrum peak search on the target angle and distance ambiguity number, which can be expressed as:

[0113]

[0114] Get the target angle estimate and the distance fuzzy number estimate Substitute it into the spectrum function to estimate the principal value distance difference and the estimated value of the target distance, which is expressed as:

[0115]

[0116] Among them, U n is the noise subspace, then the target distance estimate can be expressed as:

[0117]

[0118] The present invention provides a method for unambiguous estimation of a co-located MR-FDA-MIMO radar system. The method comprises the following steps: configuring a transceiver array of a co-located MR-FDA-MIMO radar system according to a signal carrier frequency of a preset transmitting array element; determining snapshot data of the configured co-located MR-FDA-MIMO radar system; determining a covariance matrix of the snapshot data of the co-located MR-FDA-MIMO radar system, and determining a single snapshot signal according to the covariance matrix; performing principal value distance compensation on the single snapshot signal according to a target signal power and a noise signal power based on a preset compensation vector and a principal value distance difference to obtain compensated data; using a two-dimensional spatial smoothing technique to remove signal correlation of the compensated data, and determining a covariance matrix of the single snapshot signal based on the removal result; estimating a target angle and a distance ambiguity number based on the covariance matrix of the single snapshot signal, and estimating a principal value distance difference and a target distance by using a MUSIC algorithm. When the number of array elements is constant, the determined equivalent uniform linear FDA-MIMO radar is fully utilized to expand a virtual array aperture, thereby solving the target distance ambiguity problem and breaking the limitation of the number of array elements on the estimation number, and further improving the target distance angle estimation accuracy.

[0119] The effect of the present invention is further described below in conjunction with simulation experiments.

[0120] In order to evaluate the performance of this method, a co-sited MR-FDA-MIMO radar system is considered, and its system simulation parameters are shown in Table 2.

[0121] Table 2 MR-FDA-MIMO radar system simulation parameters

[0122] Simulation parameters Numeric Simulation parameters Numeric Number of transmitting elements 4 Number of receiving elements 4 Array element spacing d 0.015m Reference carrier frequency 10GHz bandwidth 15MHz Frequency offset 37625Hz Maximum blur-free distance 30Km Maximum fuzzy number 4

[0123] Simulation experiment 1: This simulation sets up 4 targets, with target angles of 0° and main value distances of 10 km, but they are located in the first, second, third and fourth distance fuzzy areas respectively. The number of snapshots is 1000 and the signal-to-noise ratio (SNR) is 0 dB. Figure 4 and Figure 5 They are the target power spectra of uniform linear FDA-MIMO radar and MR-FDA-MIMO radar respectively. Figure 4 It can be seen that when the number of targets and the number of array elements are the same, the resolution of the uniform linear FDA-MIMO radar drops significantly, and it is completely unable to estimate the distance and angle of multiple targets and resolve the distance ambiguity. Figure 5 It can be seen that MR-FDA-MIMO radar breaks the limitation of the number of array elements on the number of estimated targets. When the number of targets and the number of array elements are the same, it can still estimate the distance and angle of multiple targets and has the ability to resolve distance ambiguity. Its performance is significantly better than that of uniform linear FDA-MIMO radar.

[0124] Simulation experiment 2: This simulation sets up 1 target with a target angle of 0° and a distance of 10Km, located in the third distance fuzzy zone. The number of snapshots is 1000, the SNR ranges from -15dB to 15dB, the step size is 5dB, and 200 Monte Carlo experiments are performed. Figure 6 and Figure 7 The angle and distance estimation accuracy of phased array (PA) radar, uniform linear FDA-MIMO radar and MR-FDA-MIMO radar are compared respectively. Figure 6 It can be seen that the angle estimation accuracy of the three radars increases with the increase of SNR. The angle estimation accuracy of PA radar and uniform linear FDA-MIMO radar is similar, while MR-FDA-MIMO radar breaks the Cramer-Rao boundary (CRLB) of angle estimation accuracy and is significantly higher than the first two radars. Figure 7 It shows that improving SNR cannot improve the range resolution of PA radar, while the range resolution performance of MR-FDA-MIMO radar is significantly better than that of uniform linear FDA-MIMO radar.

[0125] Simulation experiment three: This simulation sets up 1 target with a target angle of 0° and a distance of 10 km, located in the third distance fuzzy zone. The number of snapshots ranges from 100 to 1000, the step size is 100 times, the SNR is 0 dB, and 200 Monte Carlo experiments are performed. Figure 8 and Fig. 9 The angle and distance estimation accuracy of PA radar, uniform linear FDA-MIMO radar and MR-FDA-MIMO radar are compared respectively. Figure 8 It can be seen that the angle estimation accuracy of the three radars increases with the increase of snapshot number, but the performance improvement is small. Among them, the angle estimation accuracy of MR-FDA-MIMO radar is higher than that of the first two radars. Fig. 9It can be seen that the range resolution of PA radar is less affected by the number of snapshots, and when the number of snapshots exceeds 800, increasing the number of snapshots has a very limited effect on the range resolution of the three radars. The range resolution performance of MR-FDA-MIMO radar is significantly better than that of uniform linear FDA-MIMO radar, but it is still some distance away from CRLB.

[0126] The present invention also provides a structure of an electronic device, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus.

[0127] Memory, used to store computer programs;

[0128] The processor is used to implement the steps provided in the above method embodiment when executing the program stored in the memory.

[0129] The communication interface is used for communication between the above electronic device and other devices.

[0130] The method provided in the embodiment of the present invention can be applied to electronic devices. Specifically, the electronic device can be: a desktop computer, a portable computer, an intelligent mobile terminal, a server, etc. This is not limited here, and any electronic device that can implement the present invention belongs to the protection scope of the present invention.

[0131] The present invention also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps provided in the above method embodiment are implemented.

[0132] As for the device / electronic device / storage medium embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the specific content and beneficial effects and other related matters can be referred to the partial description of the method embodiment.

[0133] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0134] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A method for unambiguous estimation of a co-sited MR-FDA-MIMO radar system, characterized in that: include: Determine the array element position coefficients corresponding to the transmitting array and the receiving array according to the number of array elements of the transmitting array and the receiving array respectively, and configure the transmitting array and the receiving array of the co-sited MR-FDA-MIMO radar system according to the corresponding array element position coefficients; Controlling the transmitting array of the co-sited MR-FDA-MIMO radar system to transmit an orthogonal frequency modulation signal; In response to the echo signal received by the receiving array, the snapshot data of the co-sited MR-FDA-MIMO radar system, the covariance matrix of the snapshot data of the co-sited MR-FDA-MIMO radar system and the prior principal value distance are determined; according to the covariance matrix, an equivalent uniform linear FDA-MIMO radar and a differential single snapshot signal of the equivalent uniform linear FDA-MIMO radar are determined; according to the prior principal value distance, the single snapshot signal is compensated for the principal value distance to obtain compensated data; Using a two-dimensional spatial smoothing technique to remove the signal correlation of the compensated data, and determining the covariance matrix of the single snapshot signal based on the removal result; Based on the covariance matrix of the single snapshot signal, the MUSIC algorithm is used to estimate the target angle and range ambiguity number, as well as the principal value range difference and the target distance.

2. The method according to claim 1, characterized in that The signal carrier frequency of the transmitting array element is expressed as: fm=f0+DmΔf, Among them, f m represents the signal carrier frequency of the mth transmitting array element, f0 represents the frequency on the reference array element, Δf represents the frequency deviation of the array element, and D m Represents the array element position coefficient, m=1,2,…,M, and m represents the index of the transmitting array element.

3. The method according to claim 1, characterized in that The signal output data snapshot of the co-sited MR-FDA-MIMO radar system is represented as: y=ys+yn, Where y represents the snapshot data of the co-sited MR-FDA-MIMO radar system, yn represents the system noise, and ys represents the signal output data snapshot.

4. The method according to claim 1, characterized in that: Determining the equivalent uniform linear FDA-MIMO radar and the differential single snapshot signal of the equivalent uniform linear FDA-MIMO radar according to the covariance matrix includes: Performing vectorization processing on the covariance matrix to obtain a vectorized covariance matrix; The vectorized covariance matrix is ​​subjected to redundancy removal and rearrangement processing to obtain an equivalent uniform linear FDA-MIMO radar and a differential single snapshot signal of the equivalent uniform linear FDA-MIMO radar.

5. The method according to claim 4, characterized in that The single snapshot signal is represented as: Where z represents a single snapshot signal, F represents a selection matrix, represents the vectorized covariance matrix, represents the target signal, a d (r,θ) represents the transmit-receive joint steering vector of the equivalent uniform linear FDA-MIMO radar, r represents the target distance, θ represents the target angle, represents the noise signal power, and id represents the identity matrix after vectorization, redundancy removal, and rearrangement.

6. The method according to claim 1, characterized in that The compensated data is expressed as: Among them, zc represents the compensated data, z represents the single snapshot signal, g represents the compensation vector, represents the target signal, a d (Δr, p, θ) represents the compensated transmit-receive joint steering vector, Δr represents the principal value distance difference, p represents the target range ambiguity number, θ represents the target angle, represents the noise signal power, id represents the identity matrix after vectorization, redundancy removal and rearrangement, and ⊙ represents the Hadamard product.

7. The method according to claim 1, characterized in that The estimated value of the principal value distance difference is expressed as: in, represents the estimated value of the principal value distance, represents the subarray transmit-receive joint steering vector, Δr represents the principal value distance difference, represents the distance fuzzy number estimate, represents the target angle estimate, Un represents the noise subspace, and the superscript H represents the conjugate transpose operation.

8. The method according to claim 1, characterized in that The estimated value of the target distance is expressed as: in, represents the estimated value of the target distance, represents the estimated value of the principal value distance, rb represents the a priori principal value distance obtained by pulse compression, The distance fuzzy number estimate, Ru represents the maximum unambiguous number.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, for implementing any of the methods described in claims 1-8 when executing a program stored in a memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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