456 results about "Mimo radar" patented technology

Disclosed is a method for designing a sparse antenna array that includes determining a first set of separation distances among a plurality of sparse elements along an axis, wherein the first set minimises the highest radiated power of one or more sidelobes, when the beam is pointed at a boresight for a Uniform Linear Array (ULA) that has an equivalent aperture size but greater number of elements with respect to the sparse antenna array, and determining at least one second set of separation distances among the plurality of sparse elements, that minimises the highest radiated power of one or more sidelobes, when the beam is pointed at different angular directions, wherein at least one of these directions is at an edge of the field of view for the equivalent ULA, wherein the first, and at least one second set of separation distances are identical and optimised simultaneously to minimise their combined error function.

The invention discloses an FDA-MIMO radar multichannel coherent accumulation method based on distance-frequency offset compensation, and belongs to the technical field of radar moving target detection. The method comprises the following steps: obtaining an echo signal of a target by using a two-dimensional planar array FDA-MIMO radar; performing multi-channel matched filtering on the echo signal, and performing FFT (Fast Fourier Transform) at slow time to realize pulse accumulation; performing covariance matrix calculation to obtain a noise subspace and a signal subspace; searching an azimuth angle and a pitch angle of the target, and obtaining a distance-frequency offset coupling compensation vector based on characteristic decomposition; and performing multi-channel beam forming, performing coherent synthesis on multi-channel signal energy, and performing target detection by using a constant false alarm rate. According to the method, the output signal-to-noise ratio can be remarkably improved, the calculation complexity of coherent accumulation is reduced, and when an error exists in target distance estimation or a Doppler effect is generated by frequency offset, compared with a MUSIC algorithm, the method can obtain higher coherent accumulation gain.

The invention discloses a target parameter joint estimation method based on an MCCC criterion in an impulse noise environment, and belongs to the technical field of radars. According to the method, the target function based on the TALS criterion in the PARAFAC algorithm is corrected by adopting the maximum multiple correlation entropy MCCC criterion to enable the target function to be suitable for the impulse noise environment, the PARAFAC algorithm based on the MCCC criterion is derived, the algorithm is applied to bistatic MIMO radar target parameter estimation, dependence of the FLOS method on feature index priori knowledge is broken through, and joint estimation of target parameters is achieved.

The present disclosure generally relates to methods, systems, apparatuses, and non-transitory computer readable media for processing radar signals of a MIMO radar system. By dynamically accounting for environmental noise both spatially and temporally, systems of the present disclosure can make radar-based systems more accurate and robust against noised-induced false detections, especially with respect to the use of sparse-receivers. More precisely, systems of the present disclosure may first process MIMO radar return data to identify one or more range-Doppler-elevation (RDE) bins exceeding a candidate detection criteria. Each identified candidate detection RDE bin may then be processed by a second search procedure to identify any azimuth bins (of the particular candidate detection RDE bin) exceeding a confirmed detection criteria. Each identified azimuth bin indicates a confirmed detection of a scatterer (e.g., an object) whose azimuth, elevation, range, and Doppler-velocity indicated by the identified azimuth bin and its associated candidate detection RDE bin.

The invention discloses a two-dimensional smart noise interference method based on a centralized MIMO radar, and belongs to the technical field of radar communication.The method comprises the steps that down-conversion processing is carried out on radar transmitting signals intercepted by a digital radio frequency memory through a jammer, and the radar transmitting signals are subjected to down-conversion processing; periodic sampling is carried out on each pulse of a signal transmitted by an enemy through intermittent sampling to form a plurality of slices, then smart noise interference modulation is carried out in a distance dimension and a speed dimension, and finally, up-conversion processing is carried out on a modulation signal, so that a forwarding type two-dimensional smart noise interference signal is formed. After an MIMO radar receives an interference signal, a result obtained by a conventional signal processing method is seriously influenced by the interference signal generated in the invention. According to the method, smart noise interference is applied to an enemy radar signal in the distance dimension and the speed dimension, and an intensive false target is successfully generated, so that the detection of the MIMO radar on a real target is interfered.

A multi-chip MIMO radar system includes a plurality of transmitters and a plurality of receivers. Each of the pluralities of transmitters and receivers are arranged across a plurality of chips. The multi-chip MIMO radar system is configured to provide an exemplary chip synchronization such that the transmitters and receivers of each chip of the radar system are synchronized with the transmitters and receivers of every other chip of the radar system.

The invention provides a high-precision angle estimation method for a distributed millimeter wave radar network, a medium and equipment, and belongs to the technical field of radar signal processing. According to the method, a large-aperture MIMO radar system is constructed based on a plurality of small millimeter wave radars, and an initial rough angle value of a target is obtained by using two-dimensional fast Fourier transform; accurately calculating the walking position of the distance spectrum peak value of each virtual antenna according to the distance resolution of the radar and the rough angle value, extracting all distance spectrum peak value data according to the walking position, and generating a one-dimensional angle vector; performing angle dimension fast Fourier transform on the one-dimensional angle vector to generate an angle spectrum; calculating a target angle estimation value according to the angle spectrum peak value position; the above process is iteratively circulated until the error between two adjacent angle estimation values is smaller than a preset threshold value. According to the method, different types of distributed millimeter wave radar network architectures can be flexibly adapted, the precision problem caused by target distance walking is effectively eliminated, and the angle estimation precision is greatly improved.

The invention discloses a speed ambiguity resolution method suitable for 4D millimeter wave radar imaging. The method comprises the steps of 1, acquiring radar original target sampling data, and performing two-dimensional fast Fourier transform processing to obtain a target distance-Doppler matrix; carrying out constant false alarm rate detection on the target distance-Doppler matrix; 2, searching an optimal representative point as a speed representative point of the target; 3, adopting a hypothetical phase compensation speed ambiguity resolution algorithm for the speed representative point of the target to obtain a speed and a phase compensation value corresponding to the representative point; step 4, compensating all target points with phase compensation values calculated according to the representative points, and performing DOA estimation to obtain azimuth angle values; 5, coordinate transformation is carried out according to the obtained target point speed and azimuth angle value, the real position of the target under the three-dimensional coordinate system is obtained, and the representative point speed represents the real speed of the target. According to the invention, the detection capability of the MIMO radar imaging system on a high-speed target can be improved.

The invention discloses a handheld security check imaging method based on MEMS assistance, and aims to combine an MEMS sensor with an MIMO radar plate to form a handheld convenient security check imaging method with high precision and low cost according to the rapid and fine security check requirement of people in a security check place with dense people. Firstly, the radar board transmits a linear frequency modulation signal and receives an echo signal reflected by a target, and during the period, the MEMS sensor feeds back the motion track and position information of the handheld security check system in real time, and provides accurate attitude and position information. And secondly, position calibration is carried out on the track information of the MIMO radar antenna through the data of the MEMS sensor, and the zero drift of the accelerometer is compensated based on the wavelet packet change, so that the error caused by the system motion and the position change is reduced. And finally, residual phase errors are estimated and eliminated based on a particle swarm algorithm, non-contact three-dimensional imaging of the target is realized in combination with a wavenumber domain imaging algorithm on this basis, and hazardous article inspection is realized in combination with technologies such as deep learning and image recognition.

The invention relates to the technical field of beam forming, in particular to a flow antenna assisted communication sensing integrated beam forming method and device, and the method comprises the steps: building a flow antenna FAS communication channel model, and constructing a radar sensing model employing multiple input multiple output (MIMO) at a base station end; the method comprises the following steps of: establishing an optimization problem of combining port selection and beamforming under the constraint of meeting a minimum communication SNR (Signal to Noise Ratio) requirement, a minimum sensing SNR requirement and a limited port activation number by taking minimization of system transmitting power as a target; and setting constraint conditions, solving a target problem, and obtaining a communication-sensing integrated beam forming matrix. Therefore, the problems that performance coupling is aggravated and the joint design complexity is high due to the fact that the tradeoff of the communication rate and the sensing precision in the ISAC and optimization variables are increased through FAS dynamic port switching, and the performance potential is difficult to play due to the fact that the FAS extra freedom degree is not effectively combined with ISAC beam forming and waveform design are solved.

The invention discloses a non-line-of-sight moving target three-dimensional reconstruction method based on an MIMO millimeter wave radar, and is applied to the technical field of radar target detection in a complex urban environment. Aiming at the problem of difficulty in realizing three-dimensional reconstruction of a non-line-of-sight moving target in the existing radar target detection technology, the method comprises the following steps: firstly, establishing a non-line-of-sight multipath propagation model, and exporting a multipath signal model of an MIMO millimeter wave radar; the invention further provides a multipath signal departure angle (DoD) / arrival angle (DoA) unambiguous estimation algorithm, and solves the problem that a main lobe and a grating lobe are difficult to distinguish in the DoD / DoA estimation process of an existing commercial MIMO radar. And finally, proposing a path-oriented non-line-of-sight target three-dimensional positioning algorithm, respectively positioning the non-line-of-sight target by using different paths, and fusing different path positioning results to form a three-dimensional point cloud. According to the method, three-dimensional reconstruction of a plurality of non-line-of-sight moving targets can be realized, and the correlation problem between paths does not need to be considered.

The invention discloses an FDA-MIMO radar system space topology and transmit-receive parameter optimization method. The method is specifically implemented according to the following steps: step 1, establishing a distributed FDA-MIMO radar system basic model; and step 2, establishing a distributed FDA-MIMO radar system optimization model, and realizing site configuration. The problems that an existing radar system is poor in target signal receiving capacity and low in radar detection performance are solved.

The invention relates to a 4D millimeter wave MIMO radar fan blade deformation detection method and system. According to the method, a 4D millimeter wave MIMO radar antenna after layout optimization is used for transmitting a radio frequency signal to a fan blade, signal processing is carried out on the radio frequency signal reflected by the fan blade, and blade deformation detection is achieved in the horizontal angle direction and the pitch angle direction. The system provided by the invention is used for implementing the method. Compared with the prior art, the method has the advantages that the antenna array is arranged, so that the horizontal angle and the pitch angle of the fan blade are measured at the same time on the premise of minimizing the side lobe influence, the misjudgment risk is avoided, and the precision and the reliability of deformation detection of the fan blade are improved.

The invention discloses a FDA-MIMO radar multi-target distance angle joint super-resolution method and system, and mainly solves the problem that the existing phased array only depends on the angle to identify multiple targets, resulting in low resolution ability, and the implementation scheme of the method comprises the steps of obtaining FDA-MIMO radar echo data, and performing separation aliasing on the FDA-MIMO radar echo data to obtain a data matrix; performing conversion stacking on the data matrix to obtain NM * L-dimensional data, and calculating a covariance matrix of the NM * L-dimensional data; performing reverse array decoherence processing on the covariance matrix to obtain a new source signal covariance matrix; constructing a two-dimensional spatial spectrum function of a target distance and a target angle for the new source signal covariance matrix through a MUSIC algorithm; and performing spectrum peak search on the two-dimensional spatial spectrum function, and detecting a local maximum value of the two-dimensional spatial spectrum function to obtain a distance and angle joint estimation value of a plurality of targets. The method can improve the angle resolution capability of the target when the target angle interval is lower than the traditional resolution, reduces the influence of the amplitude-phase error on the resolution capability when the target distance interval is large enough, and can be used for target recognition.

The invention discloses an EPC-MIMO radar main lobe deception jamming resisting method based on a directional diagram, and mainly solves the problem that main lobe deception jamming cannot be restrained under the DOA error background in the prior art. According to the implementation scheme, array element pulse coding is carried out on a transmitted signal at a transmitting end, and matched filtering and decoding are carried out on an echo signal at a receiving end; estimating an equivalent receiving angle of transmitting and receiving spatial frequencies of a false target by utilizing characteristic decomposition of a covariance matrix of the decoded echo signal, and presetting a plurality of null regions around an estimation result; the method comprises the steps of applying constraint to wave beam response around a false target in a transmitting-receiving spatial frequency domain, constructing an optimization problem by using an iterative weight vector control method, solving the optimization problem to obtain an optimal weight vector, and completing suppression of main lobe deception interference under the DOA error background by using an optimal wave beam. According to the method, the null depth is deepened, the null area of the directional diagram is widened, the output signal to interference plus noise ratio and the interference suppression performance are improved, and the method can be used for target detection.

The present invention relates to a MIMO radar space-time-range three-dimensional joint adaptive detection method based on the LCMV criterion. The present invention first disassembles the received MIMO radar array element-pulse-range three-dimensional echo data into multiple "space-time-waveform" three-dimensional data matrices according to the waveform length, and then converts each three-dimensional data matrix into a two-dimensional data matrix as the input of the joint adaptive processing; then, a joint adaptive filter is constructed based on the LCMV criterion, and the two-dimensional data matrix is ​​subjected to joint adaptive filtering processing; finally, the result of the joint adaptive filtering processing output is used as the detection statistic to implement the threshold detection. Compared with the traditional cascade processing method of "matched filtering + beamforming + Doppler domain detection", the present invention can suppress the side lobes generated by strong targets, avoid the shielding of adjacent weak targets, suppress clutter, reduce the demand for data, and has a faster computing speed, so it has the advantage of being easy to implement in engineering.

The invention discloses a multi-target vital sign detection method for a TDM-MIMO millimeter wave radar, and the method comprises the steps: controlling a transmitting antenna to transmit a signal to a target region in a TDM-MIMO mode of the millimeter wave MIMO radar, controlling a receiving antenna to receive an echo signal reflected by the target region, and carrying out the extraction and recombination of the echo signal to form an array signal; carrying out distance FFT (Fast Fourier Transform) and carrying out static clutter filtering by using a phasor mean cancellation algorithm; performing forward and backward spatial smoothing and spatial spectrum estimation, and performing two-dimensional constant false alarm rate detection and clustering to realize two-dimensional plane positioning of a human body target; carrying out phase unwrapping and smoothing processing to obtain a phase difference value sequence; and finally, using an improved sine algorithm to guide a dung beetle optimization algorithm to carry out iterative optimization on parameters of the variational mode decomposition algorithm, and using the parameters after iterative optimization to carry out variational mode decomposition on the phase difference value sequence to obtain vital sign parameters of each human body target. The method has high environmental adaptability, and the detection reliability and automation degree are improved.

The invention provides a distributed MIMO clutter echo simulation method based on GIS information, and the method comprises the steps: obtaining the GIS information of a geographic information system, and dividing a surface scatterer irradiated by an MIMO radar into a plurality of basic scattering units based on the GIS information; calculating slope distances, Doppler frequencies, terrain elevation values and land cover types of the plurality of basic scattering units to form a scene model element set; mapping a plurality of basic scattering units to a radar resolution unit by combining a backscattering coefficient empirical model and a resolution adaptive grid mapping method according to the scene model element set; dividing the radar resolution unit into a permanent scattering area and a dynamic scattering area according to GIS information; performing clutter statistical characteristic simulation processing on the permanent scattering region and the dynamic scattering region to obtain a clutter amplitude sequence; and performing echo analysis processing on the clutter amplitude sequence in a time-frequency domain to obtain clutter echo simulation data. And the simulation precision of clutter echo simulation data is integrally improved.

The invention discloses a joint design method for an MIMO radar and interference integrated system transceiver, and belongs to the technical field of radar signal processing and electronic warfare. Aiming at the problems of spectrum resource waste, equipment redundancy and electromagnetic compatibility caused by separation of radar detection and interference functions in the prior art, the invention provides an AOFP-based combined waveform and filter design method. A multi-target optimization problem is constructed under energy constraint and peak-to-average ratio limitation, SJNR of a minimum interference target and SJNR of an IRAJ system are taken as targets, a closed-form solution is generated by using a scaling technology, fractional programming and a PML method, and dynamic balance of radar detection and interference functions is realized. The designed waveform has high anti-interference capability and concealment, supports space diversity and time-frequency joint modulation of an MIMO system, and analyzes and verifies strong target echo characteristics and interference suppression performance through a fuzzy function. The calculation complexity of the algorithm and the number of antennas are in a cubic relationship, the convergence speed is high, the comprehensive efficiency of a combat platform in a complex electromagnetic environment can be remarkably improved, and the method is suitable for a new generation of cognitive electronic warfare systems.

The invention discloses an MIMO radar three-dimensional high-resolution imaging method based on a cascade neural network. The method comprises the following steps: constructing a T-ALISTA network training data set; the method comprises the following steps of: initializing and training a T-ALISTA network; constructing a training data set to train the IT-Net; processing the radar echo data by using the trained T-ALISTA to obtain a low-quality target image; and carrying out maximum value normalization processing and conversion processing from a complex value image to a real value image on a low-quality target image # imgabs0 # output by the T-ALISTA to obtain an input image # imgabs1 # of the IT-Net. The method is used for realizing rapid, steady and high-resolution three-dimensional imaging of an aerial moving target by the MIMO radar under a system error condition; and rich and key feature information is provided for early warning detection, classification identification and the like of the target.

The invention provides a distributed millimeter wave radar network-oriented DOA estimation method, a medium and equipment, and belongs to the technical field of radar signal processing. According to the method, after a large-aperture MIMO radar system is formed based on a plurality of small millimeter wave radars, a two-dimensional single-snapshot sparse array signal model is constructed by using a steering vector of a two-dimensional MIMO equivalent virtual plane array, and data interpolation and extrapolation processing are performed on aperture missing existing in a sparse array by constructing a block Hankel matrix and applying a matrix completion technology. On the basis, a fast two-dimensional angle estimation algorithm based on phase coherence factor weighting is adopted, and efficient joint estimation of the azimuth angle and the pitch angle of the target is achieved. The method can be flexibly applied to different types of distributed millimeter wave radar networks, effectively overcomes the interference effect of DOA estimation sidelobes and grating lobes in the prior art, and improves the signal-to-noise ratio level of array response.

The invention provides a target translation compensation and three-dimensional imaging method and system for a close-range millimeter wave MIMO radar, and the method and system achieve the high-quality real-time three-dimensional imaging. The method comprises the following steps: receiving echo data and movement speed of a tested person, and carrying out phase calibration from multi-station sampling to single-station sampling on the echo data; performing two-dimensional Fourier transform and motion compensation in x and y directions on the echo data after phase calibration based on the motion speed of the tested person; performing two-dimensional inverse Fourier transform on the echo data after two-dimensional Fourier transform and operation compensation in the wave number domain # imgabs0 # and # imgabs1 # directions; performing coherent superposition on the echo data after the two-dimensional inverse Fourier transform to obtain echo data after motion compensation of the tested person; based on a static target three-dimensional imaging algorithm principle, processing the echo data after motion compensation of the tested person to obtain two-dimensional images of each distance direction plane; and performing traversal synthesis processing on the two-dimensional image in each distance direction plane to obtain a three-dimensional image of the tested person.

The embodiment of the invention relates to the technical field of radars, and discloses an MIMO radar emission sequence set design optimization method, which comprises the following steps: constructing a signal model designed based on an AF emission sequence set for an MIMO radar system, selecting ISL of minimizing local AAF and CAF as an optimization criterion, selecting an energy constraint and a dynamic range constraint as constraint conditions, and selecting an energy constraint and a dynamic range constraint as constraint conditions; establishing a four-order non-convex constraint optimization problem; decomposing the fourth-order non-convex constraint optimization problem into a plurality of sub-problems which can be iteratively solved by utilizing an MBI algorithm; sequentially solving the sub-problems by means of CVX to obtain a preliminary solution; and continuously adjusting a search direction and a step length by using a BLS algorithm, and carrying out iterative optimization on the approximate solution until an Armijo condition is met, thereby obtaining a global optimal solution meeting a design requirement, and further designing a radar emission sequence set with good related characteristics, thereby improving the target detection capability, the anti-interference capability and the resolution of the MIMO radar system.

The invention discloses a non-orthogonal waveform MIMO radar imaging method based on deep learning, and the method comprises the following steps: constructing an MIMO radar echo signal model, and obtaining a target echo signal in a whole imaging scene; separating signals of different waveforms in the target echo signal under the condition that the transmitted waveform satisfies an ideal orthogonal condition to obtain waveform vectors corresponding to the different waveforms, and performing azimuth compression to obtain an ideal target image of the MIMO radar; taking frequency domain echo signals at different receiving array elements in an MIMO radar echo signal model and the ideal target image as a training set, and training the constructed deep network model to obtain a trained deep network model; performing target imaging on the actual target echo signal by using the trained deep network model; according to the invention, the echo signal is processed through the trained deep network echo, the coupling interference between waveforms can be effectively suppressed, and the target high-resolution image can be efficiently acquired.

The invention belongs to the technical field of radar signal processing and imaging, and particularly relates to a distributed MIMO radar imaging method based on multi-technology fusion, which comprises the following steps: S1, constructing a distributed MIMO radar array: constructing a distributed array consisting of L identical MIMO radar units, each unit comprising M transmitting antennas and N receiving antennas; the multi-radar synchronous imaging method is characterized in that each radar unit adopts an offset frequency orthogonalization design, signals of each radar unit and different transmitting antennas in the same unit are mutually orthogonal in a time domain and a frequency domain by elaborately setting the offset frequency of each transmitting antenna, a virtual array is equivalent to a uniform linear array, and multi-radar synchronous imaging is realized by utilizing a high-precision synchronous control mechanism. According to the method, the equivalent aperture is greatly expanded through cooperative work of the distributed MIMO radar arrays, so that the angular resolution is remarkably improved, the accuracy and reliability of echo signals are guaranteed by adopting a unique orthogonal signal design, and the imaging stability is improved.

A method of operating a radar system (14), in particular a radar system (14) for a vehicle (10), a radar system (14), a driver assistance system (12) and a vehicle (10). In the method, at least one electromagnetic radar signal (22) is transmitted from at least one transmitting antenna element (34) of the radar system (14). At least one electromagnetic echo signal (40) generated by at least one radar signal (22) reflected from at least one target (20) in a field of view of the radar system (14) is received by at least one receiving antenna element (38) and converted into received data (72) adapted for signal processing. The radar system (14) is operated as a MIMO radar comprising a plurality of transmit antenna elements (34) and a plurality of receive antenna elements (38), where the transmit antenna elements (34) and the receive antenna elements (38) generate a virtual antenna array having a plurality of virtual antenna elements for receiving echo signals (40) during MIMO operation of the radar system (14). For at least a portion of the virtual antenna element, amplitude information and phase information are determined from at least a portion of the received data, respectively, by performing at least one two-dimensional fast Fourier transform. At least one array data set is determined that includes at least amplitude information and phase information for at least a portion of the virtual antenna elements. At least a portion of the data of the at least one array data set is fed to at least one neural network (64), with which at least one piece of positional information of the at least one detected target (20) is determined.

The invention belongs to the field of signal processing, particularly relates to a signal processing method, system and equipment based on an MIMO radar, and aims to solve the problem of limited detection precision caused by insufficient utilization of multi-channel signals and simple fusion strategy in the prior art. The method comprises the following steps: obtaining a target multi-channel echo signal, carrying out distance and angle processing, extracting phase change by using phase unwrapping, carrying out two-stage weighted fusion based on slope entropies of a receiving channel and a transmitting channel in sequence, obtaining a micro-motion signal, carrying out variational mode decomposition and frequency band matching screening, and reconstructing a final output signal. According to the method, the problem of insufficient utilization of multi-channel information is effectively overcome, and the signal noise immunity and the micro-motion feature fidelity are remarkably improved through a double fusion strategy, so that the detection and recognition precision of a weak target is improved.

The invention discloses a millimeter wave radar MIMO multichannel signal sparse separation reconstruction method and system, belongs to the technical field of MIMO radar target detection, and solves the problem of how to improve the MIMO multichannel signal separation efficiency and accuracy, and the method comprises the steps: obtaining a millimeter wave radar echo signal, and converting the millimeter wave radar echo signal into a 4D matrix; performing fast Fourier transform on the 4D matrix to obtain a frequency domain 4D complex matrix and distance-Doppler spectrum data; further obtaining distance-Doppler unit index value pairs corresponding to all peak values; inputting the distance-Doppler unit index value pair into the frequency domain 4D complex matrix to obtain an MIMO multichannel signal two-dimensional matrix; based on the sparse number matrix corresponding to the virtual array, combining with the MIMO multichannel signal two-dimensional matrix, obtaining a two-dimensional sparse reconstruction matrix through numerical relation mapping, and performing vacancy position zero padding operation on the two-dimensional sparse reconstruction matrix to obtain a two-dimensional reconstruction matrix; according to the invention, the efficiency and accuracy of MIMO multi-channel signal separation are improved.

The invention provides a joint optimization method and system for MIMO radar waveform design and antenna array arrangement, and belongs to the technical field of radar signal processing. A covariance matrix of a transmitting signal set is converted into a transmitting weight matrix of a time domain, and matching optimization of a radar waveform and an expected beam pattern is realized based on the transmitting weight matrix; according to the method, the directional diagram performance of the optimized radar waveform of the time domain in actual emission can be ensured, meanwhile, the influence of an antenna array arrangement vector on an emission beam pattern is considered, joint optimization is carried out on the radar waveform corresponding to an emission weight matrix and the antenna array arrangement vector, collaborative optimization between waveform design and array design is achieved, and the method has the advantages of being high in practicability and high in practicability. The overall performance potential of the system can be fully excavated, and the actual demand of a target detection task in a complex environment can be well met.

A TDM MIMO FMCW radar comprises at least one row of physical receivers with a first spacing (dr) in a first direction, and further comprises a plurality of physical transmitters arranged with a second spacing (dt) in said first direction. To determine whether a peak in an angle spectrum corresponds to a direct reflection or a first-order multipath artefact, an inverse phase-shift vector corresponding to a phase ({circumflex over (ϕ)}1) of the peak is applied and a constant signal with the amplitude of the peak is subtracted. To the thus obtained intermediate signal (v), a further inverse phase-shift vector—now corresponding to an offset phase (Δ{circumflex over (ϕ)}) of the two leading peaks of the angle spectrum—after which a constant signal is subtracted. It is then detected whether the thus obtained test signal (w) has any non-noise content. If yes, the peak corresponds to a multipath artefact, and otherwise to a direct reflection.