15 results about "Bistatic mimo radar" patented technology

The present invention discloses a high-resolution, wide-band imaging method for an airborne bistatic MIMO radar, comprising the following steps: obtaining an optimal pulse coding coefficient; encoding a transmitted signal to obtain a coded signal; performing matched filtering on an aliased signal received from a transmitting array element to obtain an echo signal; vectorizing the received signal to obtain a vectorized aliased signal; performing pulse coding compensation on the aliased signal to obtain a compensated echo signal; solving for the common weights corresponding to the echo data matrix to obtain the optimal weights; performing fuzzy echo suppression on the echo data matrix using the optimal weights to obtain a fuzzy-suppressed echo signal; removing the Doppler center fuzziness of the fuzzy-suppressed echo signal from the first receiving array element to obtain a compensated signal; and performing azimuth focusing on the compensated signal to obtain a final unambiguous image. The present invention can effectively suppress range fuzziness in a bistatic system, reduce the impact of fuzzy echoes, eliminate Doppler center fuzziness, and improve imaging quality.

The application relates to a bi-static MIMO radar correction distance deviation method based on algebraic analysis, which comprises the following steps: obtaining a target echo signal of a bi-static MIMO radar; making a receiving beam point to a target according to a known target receiving angle, selecting an arbitrary angle of a transmitting beam to point to, sequentially performing receiving beam forming and pulse synthesis processing on the target echo signal to obtain an initial pulse synthesis output signal; calculating and correcting a time difference according to a spatial phase deviation caused by the transmitting beam pointing to a target transmitting angle, to obtain a corrected time difference; calculating a distance difference according to a difference between the initial pulse synthesis output signal and a sum of a real distance and the target; calculating a target transmitting angle according to an algebraic expression of the corrected time difference and the distance difference and the corrected time difference and the distance difference; and calculating a real position of the target by using the target transmitting angle. The method simplifies a traditional bi-static MIMO radar signal processing flow, reduces an operation amount, and has stable target detection performance.

The invention discloses a centralized array amplitude-phase error angle estimation method, which comprises the following steps of: modeling received signals with amplitude-phase errors of all array elements of a transmitting array and a receiving array aiming at a bistatic MIMO radar array; moving the receiving array and the transmitting array to obtain a steering vector matrix of the receiving and transmitting array before and after moving; obtaining an estimated value of a steering vector matrix of the transceiving array before and after movement through PARAFAC decomposition of the received signals before and after movement; constructing a synthetic steering vector matrix of the transmit-receive array; performing line transformation on lines with equal amplitude-phase error coefficients in the synthetic steering vector matrix of the transceiving array, and constructing a transformed synthetic steering vector matrix; then matrix identical transformation is carried out on the column vectors corresponding to the targets to obtain a rank loss intermediate matrix and an amplitude-phase error coefficient vector of the transmit-receive array; and constructing a spectrum peak function, obtaining a 2D-DOD estimated value and a 2D-DOA estimated value through two-dimensional space search, and carrying out target pairing.

This invention discloses a centralized array partial amplitude and phase error self-correction angle estimation method, comprising: constructing a received signal model for a bistatic MIMO radar array where some array elements of the transmitting and receiving arrays have amplitude and phase errors; performing identity transformations on the steering vector matrices of the receiving and transmitting arrays respectively to obtain the rank-loss intermediate matrices of the receiving and transmitting arrays; obtaining the estimated value matrices of the steering vector matrices of the receiving and transmitting arrays by performing PARAFAC decomposition on the radar received signal model; performing eigenvalue decomposition on the covariance matrix of the estimated value matrices to obtain the noise subspace corresponding to the received signals of the receiving and transmitting arrays; obtaining the estimated values ​​of the amplitude and phase error vectors of the receiving and transmitting arrays using the relationship between eigenvectors and eigenvalues; constructing a spectral peak function using the estimated values ​​of the amplitude and phase error vectors of the receiving and transmitting arrays, obtaining the 2D-DOD estimate and the 2D-DOA estimate through two-dimensional space search, and performing target pairing based on the maximum likelihood function.

The application provides a low-complexity target DOD-DOA and Doppler frequency joint estimation algorithm based on space-time nested sampling, and the joint estimation algorithm comprises the following steps: step 1: configuring a bistatic MIMO radar system into a space-time nested sampling model, and sampling a received signal {x q (l)} by using the space-time nested sampling model; q Step 2: performing multi-stage delay sampling on the received signal {x q (l)} to obtain {y(l)}; step 3: performing matched filtering on the received signal {y(l)} to obtain {y(t)}; step 4: solving a target echo signal covariance matrix R; step 5: vectorizing and de-redundantizing the target signal covariance matrix, and obtaining a new observation signal according to the obtained observation signal; step 6: performing three-dimensional Toeplitz matrix iterative reconstruction on the new observation signal to obtain an equivalent covariance matrix R xx in a virtual domain; and step 7: solving DOD-DOA and Doppler frequency parameters of the target by using an improved multi-dimensional ESPRIT algorithm.

The application discloses a target parameter estimation method based on a bounded nonlinear function in an impulsive noise environment and belongs to the technical field of radar signal processing. The bounded nonlinear function, that is, a Sigmoid function, is used for suppressing an Alpha stable distribution noise, a target function based on a TALS criterion in a PARAFAC algorithm is modified based on the bounded nonlinear function so as to be applicable to the impulsive noise environment, a PARAFAC algorithm based on the bounded nonlinear function is derived, the algorithm is applied to target parameter estimation of a bistatic MIMO radar, joint estimation of target parameters is realized, and automatic pairing can be realized.

The present invention provides a method for jointly estimating the DOD and DOA of an arbitrary array bistatic MIMO radar, comprising the following steps: constructing an arbitrary array bistatic MIMO radar system model including a smart reflector; after obtaining a received signal using the radar system in step S1, obtaining a covariance matrix of the received signal after matched filtering by establishing a signal model, defining a direction vector, and a channel matrix; estimating the 2D-DOD angle using a propagation operator algorithm; and obtaining a 2D-DOA angle estimate by combining the 2D-DOD angle obtained by the propagation operator algorithm. The present invention proposes a method for jointly estimating the angle of departure and angle of arrival of an arbitrary array bistatic MIMO radar using a smart reflector. Both the transmitting antenna array and the receiving antenna array are arbitrary array flow types, and the smart reflector can ensure that the signal reaches the receiving array even when the signal is blocked by obstacles.

The invention discloses a target parameter estimation method based on a bounded nonlinear function in an impulse noise environment, and belongs to the technical field of radar signal processing. According to the method, a bounded nonlinear function, namely a Sigmoid function, is adopted to suppress Alpha stable distribution noise, a target function based on a TALS criterion in a PARAFAC algorithm is corrected based on the bounded nonlinear function to enable the target function to be suitable for an impulse noise environment, the PARAFAC algorithm based on the bounded nonlinear function is derived, the algorithm is applied to bistatic MIMO radar target parameter estimation, and the target parameter estimation accuracy of the bistatic MIMO radar is improved. Joint estimation of target parameters is realized, and automatic pairing can be realized.

This invention discloses a method for multi-channel coherent accumulation and sidelobe suppression in bistatic MIMO radar, applied in the field of radar technology. It addresses the problems of high computational complexity and accumulation sidelobes in multi-channel accumulation methods based on ergonomic search (ES). First, this invention utilizes Radon-Fourier Transform (RFT) to complete signal accumulation within a channel, and designs a fast multi-channel coherent accumulation method based on the geometric topology between the bistatic MIMO radar and the target. Second, it designs an accumulation sidelobe suppression method. By analyzing the main lobe and sidelobe distribution characteristics of the multi-channel accumulation output, a main lobe energy window function is designed to retain the main lobe energy in the multi-channel accumulation output, and the accumulation sidelobe energy is suppressed based on the point spread response function. The method of this invention can achieve fast coherent accumulation of multiple channels in bistatic MIMO radar and suppress accumulation sidelobes.

The invention relates to a centralized array mutual coupling self-correction angle estimation method, which comprises the following steps: aiming at a bistatic MIMO (Multiple Input Multiple Output) radar array with a mutual coupling effect, constructing a received signal model based on a mutual coupling matrix of a transmitting array and a receiving array; performing PARAFAC decomposition on the received signal model to obtain estimated value matrixes of steering vector matrixes of a receiving array and a transmitting array; performing matrix transformation by utilizing the mutual coupling matrix of the receiving array and the transmitting array and combining the mutual coupling coefficient matrix, and constructing a rank loss intermediate matrix of the receiving array and the transmitting array; obtaining an estimated value of a mutual coupling coefficient vector of the receiving array and the transmitting array by using a relationship between the feature vector and the feature value; constructing a spectrum peak function by using the estimation values of the mutual coupling coefficient vectors of the receiving array and the transmitting array, and obtaining a 2D-DOD estimation value and a 2D-DOA estimation value through two-dimensional space search; and constructing a maximum likelihood function of the received signal, and performing target pairing on the 2D-DOD estimated value and the 2D-DOA estimated value by using the maximum likelihood function.

This invention discloses a centralized array amplitude and phase error angle estimation method, comprising: for a bistatic MIMO radar array, modeling the received signals with amplitude and phase errors for all elements of the transmitting and receiving arrays; moving the receiving and transmitting arrays to obtain the steering vector matrices of the transmitting and receiving arrays before and after the movement; obtaining the estimated values ​​of the steering vector matrices of the transmitting and receiving arrays before and after the movement by performing PARAFAC decomposition on the received signals before and after the movement; constructing the synthetic steering vector matrix of the transmitting and receiving arrays; performing row transformations on the rows with equal amplitude and phase error coefficients in the synthetic steering vector matrix of the transmitting and receiving arrays to construct the transformed synthetic steering vector matrix; then performing matrix identity transformations on the column vectors corresponding to each target to obtain the rank-loss intermediate matrix of the transmitting and receiving arrays and the amplitude and phase error coefficient vector; constructing a spectral peak function, obtaining the 2D-DOD estimate and the 2D-DOA estimate through two-dimensional space search, and performing target pairing.

The present invention discloses an angle estimation method for MIMO radar with element failure based on factor matrix prior. The method comprises the following steps: performing matched filtering on a received signal of a bistatic MIMO radar with element failure to obtain an output signal #imgabs0# of a virtual array and calculating a virtual array covariance matrix #imgabs1#; constructing a fourth-order covariance tensor #imgabs2# and expressing it as a tensor CANDECOMP / PARAFAC decomposition model; establishing a tensor filling model with factor matrix prior constraints; converting the tensor filling model into an unconstrained augmented Lagrangian function form; iteratively solving the augmented Lagrangian function using an ADMM algorithm, and obtaining a factor matrix U at the end of the iteration. (1) , U (2) and the diagonal matrix Δ (3) , Δ (4) The complete covariance tensor #imgabs3# is constructed and then restored to the complete covariance matrix R through a symmetric Hermitian expansion. Finally, the ESPRIT algorithm is used to estimate the target angle. This method can effectively recover missing data for multiple slices in the fourth-order covariance tensor, improving the angle estimation performance of MIMO radars under array element failure.

The application discloses a target parameter joint estimation method based on an MCC criterion in a pulse noise environment and belongs to the technical field of radars. The application adopts a maximum complex correlation entropy (MCC) criterion to correct a target function based on a TALS criterion in a PARAFAC algorithm so as to make the target function applicable to an impulse noise environment, deduces a PARAFAC algorithm based on the MCC criterion, and applies the algorithm to target parameter estimation of a bistatic MIMO radar, breaks through the dependence of a FLOS method on prior knowledge of characteristic indexes, and realizes joint estimation of target parameters.

The present invention relates to a near-field polarization MIMO radar parameter estimation method based on an accurate model. The method comprises the following steps: establishing a bistatic MIMO radar system, and estimating a transmission angle, a reception angle, a transmission polarization angle, and a reception polarization angle in the bistatic MIMO radar system using polarization information. The entire process does not require spectral peak searching, and is highly efficient. The estimated parameters can be automatically paired, have no phase ambiguity problem, and have high accuracy. The method is also applicable to non-uniform linear arrays with arbitrary array element spacing and phase uncertainty.

The present invention relates to a near-field polarization MIMO radar parameter estimation method based on parallel factor decomposition. A system model of a bistatic MIMO radar based on a uniform linear array of crossed dipole-magnetic loop antennas is established. The transmitting end comprises a uniform linear transmitting array composed of 2M+1 crossed dipole-magnetic loop antennas, and the receiving end comprises a uniform linear receiving array composed of 2N+1 crossed dipole-magnetic loop antennas. The spacing between transmitting array elements and the spacing between receiving array elements are represented by dt and dr, respectively. K uncorrelated near-field narrowband fully polarized targets are located. The two-dimensional transmitting angle and the two-dimensional receiving angle of the kth target are represented by θ tk and θ rk Represented by k = 1, 2, ... K, this method can accurately calculate the two-dimensional transmission angle, two-dimensional receiving angle, two-dimensional transmission polarization angle, two-dimensional receiving polarization angle and target position coordinates under the premise of a uniform linear array of cross-dipole-magnetic ring antenna. The method is simple and flexible.