281 results about "Mimo radar" patented technology

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.

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 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 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 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 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.

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 method and apparatus for separating transmission channels of a DDMA-MIMO radar, a device, and a storage medium. The method comprises: dividing a Doppler frequency domain into N transmission channels according to the number M of transmitters comprised in a DDMA-MIMO radar (S110); establishing an initial correspondence between the M transmitters and any M transmission channels (S120); determining measured range-Doppler amplitude information and reference range-Doppler amplitude information corresponding to the N transmission channels (S130); determining correlation information between the measured range-Doppler amplitude information and the reference range-Doppler amplitude information (S140); and determining a target correspondence between each transmitter and transmission channel on the basis of the correlation information and the initial correspondence (S150).

The invention discloses a UAV positioning and joint deployment and resource allocation method based on a radar, and relates to the technical field of UAV communication, the angle of a UAV relative to the radar is measured by deploying an EMVS-MIMO radar, the distance is determined by combining pulse ranging, and the three-dimensional position of the UAV can be estimated; according to the method, UAV deployment and GU association are optimized based on a BCD method, firstly, rapid convergence of a particle swarm algorithm and global optimization capacity of a grid search algorithm are combined, and UAV deployment is optimized; then, recalculating the GU association according to the new UAV deployment; a constrained particle swarm optimization algorithm is adopted to optimize the UAV transmitting power, and a variable learning rate is introduced to dynamically adjust the inertia weight, so that particles are helped to find a globally optimal solution; based on different requirements of communication and positioning GU on the bandwidth, a greedy algorithm is adopted to allocate the bandwidth of the UAV, and the fairness between the GUs is ensured.

The invention relates to the technical field of slope stability monitoring, and discloses a slope stability monitoring and early warning device based on intelligent sensing, the slope stability monitoring and early warning device comprises a slope body, a detection mechanism is arranged outside the slope body, and the monitoring mechanism comprises a GNSS displacement monitoring unit, a fiber grating stress sensor, an MIMO slope radar and an environment sensor assembly. Through multi-source heterogeneous data fusion: through the mu s-level time synchronization (PTP protocol) of GNSS (+ / -2.5 mm precision), MIMO radar (10-second sampling) and fiber bragg grating (+ / -1pm demodulation), the problem of data islands of traditional monitoring equipment is solved, the space-time alignment precision is improved to an engineering level standard, LSTM (50 units) is dynamically optimized through a hybrid model, and short-time risks such as displacement rate abrupt change are captured (MAElt is predicted in 12 hours; 0.3 mm), XGBoost quantifies the rainfall contribution degree through an SHAP value, long and short term risk coupling analysis and a dynamic weight switching mechanism are achieved, when an LSTM error suddenly increases, an abnormal detection mode is automatically switched, and the early warning response speed is higher.

A method, a sensor system, and a non-transitory computer readable medium are provided to determine the angle of arrival of signal 300 reflected of a target object 302. The method involving receiving a plurality of incident signals reflected from a target at a plurality of receiver antennas 304, identifying with a processor a subset of receiver antennas (404. Fig 4) from the plurality of receiver antennas when the target is in a near filed of the plurality of receiver antennas. The processor performs angle of arrival (AOA) processing on respective incident signals of the subset of receiver antennas to determine the angle of arrival of the signal. The method preferably determining an elevation and azimuth angle of the target based on the angle of arrival. The plural antenna are preferable part of a switched antenna array. The receiver antennas preferably being part of a multiple input multiple output (MIMO) radar and the subset corresponds to a virtual array formed by the MIMO radar. Preferably using all the plurality f antennas to perform AoA determination when the target is determined to be in the far field of the radar.

The embodiment of the invention provides a near-field MIMO radar data processing method based on multistage background suppression and target enhancement, and is applied to the technical field of radar signal processing. The method comprises the following steps: acquiring a real-time background template and a real-time image frame of a target scene; calculating to obtain differential image data corresponding to the real-time image frame based on the real-time background template and the real-time image frame; performing Gaussian filtering processing on the difference image data to obtain Gaussian filtering image data; performing morphological processing on the Gaussian filtering image data to obtain morphological image data; performing target enhancement processing on the morphological image data to obtain target enhanced image data corresponding to the real-time image frame; and outputting the target enhanced image data. The technical effect of improving the radar imaging precision is achieved.

The invention relates to the determination of the angle of an obstacle with respect to a radar system. Especially the invention is concerned with the transformation of radar data into the angle domain. A method for transforming radar data of a coherent MIMO radar system to the angle domain is proposed. The coherent MIMO radar system comprises transmitter antennas (Tx) and receiver antennas (Rx) spanning a virtual 2D aperture wherein two lines defining two physical directions exist, which are not collinear and wherein a group of said antennas is associated with each of said two lines, and wherein the antennas of each of said two groups are spaced apart from each other mainly along the physical direction associated with the respective line of said two groups, where in the calculations to transform the received data from a delay / Doppler domain to an angle domain is carried out using a parameterization in a coordinate system that is a dual basis to a basis constructed from the two physical directions and a third direction being perpendicular to the first physical direction and said second physical direction, and wherein the origin is chosen to be the point of intersection of the lines defined by the two physical directions or the midpoint of the line segment connecting the points of closest contact of these two lines.

This invention discloses a distributed MIMO radar resource allocation method for integrated reconnaissance, interception, and communication, belonging to the technical field of radar resource allocation. It aims to solve the performance balance problem under multi-task coordination in distributed MIMO radar air combat scenarios. An integrated reconnaissance, interception, and communication adversarial scenario is constructed, using the lower bound of position estimation error (SPEB), missile detection probability, and inter-node communication capacity as performance evaluation indicators for reconnaissance, interception, and communication, respectively. Then, with the goal of minimizing the total system transmit power, a model is constructed by combining relevant performance constraints and node task rules. Finally, the model is transformed into a mixed-integer second-order cone programming problem, and the non-convex terms are convexified using the McCormick envelope method. A numerical solution is obtained based on the CVX solver in MATLAB, achieving joint optimization of node task allocation and power allocation. This invention reduces the total transmit power while satisfying three types of performance requirements, achieving efficient waveform resource scheduling and improving the practicality and robustness of radar countermeasures.

The present invention discloses a MIMO radar sparse array optimization method based on a sleep monitoring scenario. The sparsity of the array elements is determined in combination with the actual sleep scenario, and the two-dimensional beam angle is constrained. The full angle scan is achieved by changing the beam pointing within the constrained angle, and the highest sidelobe level value of the directional pattern under all angle pointing is obtained. The multi-objective particle swarm iterative model is used to solve the optimal array element spacing, and the excitation coefficient is solved in combination with the convex optimization algorithm, and finally the array element position and excitation coefficient matrix are obtained. Compared with the uniform array, this method reduces the number of array elements, reduces the hardware implementation cost, weight and pressure, and improves the angular resolution; compared with the traditional sparse array algorithm, this method can determine the sparsity of the array elements in combination with the actual sleep scenario, and solves the problem that when the beam pointing changes in the traditional sparse array, the directional pattern will have high sidelobes and large grating lobes, ensuring that the directional pattern under all angle pointing within the constraint range has a low sidelobe level.

The invention relates to a two-dimensional staggered array MIMO (Multiple Input Multiple Output) radar system for monitoring dynamic deformation of a bridge, which realizes decoupling of spatial resolution and time resolution by adopting a two-dimensional staggered array MIMO radar hardware architecture and replacing traditional mobile synthetic aperture with static virtual aperture synthesis through integrated design. According to the system, a continuous virtual area array is synthesized through transmitting and receiving arrays which are in non-uniform sparse arrangement, and high-resolution three-dimensional imaging of a bridge monitoring area is realized in combination with an FMCW signal processing and near-field three-dimensional imaging algorithm; and carrying out pixel-level processing on the serialized three-dimensional complex image by using a rapid time sequence interference and deformation extraction module to obtain a high-precision deformation sequence. The method does not need a mechanical scanning part, has the advantages of high environmental robustness, low hardware cost, flexible deployment and the like, and can provide panoramic and high-precision four-dimensional dynamic deformation field data for bridge structure state evaluation.

The invention discloses a high-degree-of-freedom MIMO radar waveform design method capable of accurately controlling ISL, and relates to the technical field of radars, and the method comprises the steps: S1, carrying out MIMO radar constant modulus waveform design modeling, and constructing a bivariate problem under CMC and CSC constraints; s2, introducing a penalty mechanism, constructing a unified constraint space, and converting a bivariate problem into an unconstrained optimization problem; and S3, calculating the gradient of the objective function of the converted problem in the unified constraint space, and then using an adaptive conjugate gradient algorithm to optimize the two variables in parallel to solve. According to the invention, the problem can be directly solved without loosening, and the DOF of waveform design can be enhanced.

The application belongs to the field of signal processing, and particularly relates to a signal processing method, system and device based on MIMO radar, aiming to solve the problem of insufficient utilization of multi-channel signals and simple fusion strategy in the prior art, which limits the detection accuracy. The application comprises the following steps: obtaining target multi-channel echo signals and performing distance and angle processing, extracting phase changes by using phase unwrapping, performing two-stage weighted fusion based on the slope entropy of the receiving channel and the transmitting channel in sequence, obtaining micro-motion signals, performing variational mode decomposition and frequency band matching screening on the micro-motion signals, and reconstructing the final output signals. The application effectively overcomes the problem of insufficient utilization of multi-channel information, significantly improves the signal noise immunity and micro-motion feature fidelity through the double fusion strategy, and thus improves the detection and recognition accuracy of weak targets.

The present application relates to a MIMO radar multi-target detection method and system based on strong target restriction, which designs a beam weight matrix solving method with strong target restriction on the basis of a MIMO radar multi-target detection method based on reinforcement learning, takes out possible strong targets from the detection results of the MIMO radar, calculates the power gain restriction values corresponding to each strong target, designs a beam optimization scheme with strong target restriction and solves the beam weight matrix by using a convex optimization toolbox. During detection, the radar waveform corresponding to the transmission beam weight matrix is used, the Wald type statistics of the radar echo is calculated, the state calculation and action selection are performed, the angle unit to which the beam pattern of the MIMO radar needs to be focused is selected, and finally the beam weight matrix of the next detection time is quickly solved according to the beam weight matrix solving method with strong target restriction, so as to improve the detection performance of the MIMO radar on weak targets.

The application discloses a STCA-MIMO radar anti-interference method based on nonlinear time delay, which comprises the following steps: calculating target echo signals based on nonlinear time delay of transmitting array elements; carrying out digital mixing and matching filtering on the target echo signals to obtain preprocessed signals; determining a first transmitting steering vector and a first receiving steering vector according to the preprocessed signals; calculating a covariance matrix of STCA-MIMO radar system receiving data; calculating an adaptive weight vector by using a robust direct data domain beam forming technology based on the covariance matrix and an actual receiving-transmitting joint steering vector of a target; calculating a first receiving-transmitting joint steering vector of the STCA-MIMO radar system; and carrying out beam forming by using the first receiving-transmitting joint steering vector and the adaptive weight vector. The application can effectively suppress interference signals in the main lobe of the STCA-MIMO radar, and solves the problem of the decline of interference suppression performance in the prior art when the interference is located near the distance grating lobe of the main lobe of the real target.

The invention discloses a TDM-MIMO radar Doppler phase offset compensation method based on iteration, and the method comprises the steps: carrying out the equivalent conversion of a TDM-MIMO radar model into a one-transmitting-multiple-receiving virtual array model, building a signal receiving model of a virtual array, and obtaining a beat signal; constructing a target echo space-time joint matrix; constructing an airspace signal vector based on the target initial Doppler frequency; and performing iterative estimation on target angle estimation and Doppler frequency, and estimating the angle by using a phase offset compensation result. According to the method, the Doppler frequency is scanned more meticulously by constructing the Doppler frequency scanning manifold matrix, the Doppler frequency dimension and the angle dimension are decoupled, the space-time combined two-dimensional estimation is converted into two one-dimensional estimation, and the accurate Doppler frequency and angle are obtained after few times of iteration.

This application discloses a method for selecting a fully connected network structure for distributed MIMO radar target positioning, relating to the field of signal processing technology. This application includes collecting the target's echo signal and arranging it into a column of received signals in the order of signal sampling values; processing the received signals and calculating the maximum likelihood estimate of the time delay of each signal path; integrating the time delay estimates of all paths into an estimation vector, and using the FCN as an estimator based on the estimation vector to obtain the final target object position estimate; deriving a mean square error bound for a given FCN, training set, and training method, and constructing an optimization problem for network structure design based on the mean square error bound; and using a genetic algorithm to solve the optimization problem for network structure design and obtain the optimal FCN structure. The FCN structure selected in this application achieves better estimation performance.

The present invention discloses a multi-channel coherent accumulation method of an FDA-MIMO radar based on range-frequency offset compensation, which belongs to the technical field of radar moving target detection. The present invention comprises: obtaining the echo signal of the target by using a two-dimensional planar array FDA-MIMO radar; performing multi-channel matched filtering on the echo signal, and performing FFT transformation in slow time to realize pulse accumulation; then performing covariance matrix calculation to obtain the noise subspace and signal subspace; then performing azimuth and elevation angle search of the target, and obtaining the range-frequency offset coupling compensation vector based on eigendecomposition; multi-channel beamforming, coherently synthesizing the multi-channel signal energy and using a constant false alarm rate to detect the target. The present invention can significantly improve the output signal-to-noise ratio and reduce the computational complexity of coherent accumulation. Moreover, when there is an error in the target distance estimation or the Doppler effect is generated by the frequency offset, the present invention can obtain a higher coherent accumulation gain than the MUSIC algorithm.

The application provides a FDA-MIMO radar gridless target parameter estimation method based on a single base plane array, relates to the technical field of array signal processing, constructs a single base plane array FDA-MIMO radar system, and the transmitting end and the receiving end of the radar system are composed of a uniform plane array; a receiving signal model is established based on the radar system, the model is vectorized, a selection matrix is introduced to construct an angle-distance decoupling receiving signal model; the covariance matrix of the receiving signal model is calculated; a low-rank matrix reconstruction optimization problem suitable for the model is established according to the covariance matching criterion; the optimization problem is solved by the idea of alternating projection by using the properties of the covariance matrix; the information of the angle theta and the distance r is estimated by the multiple signal classification method according to the covariance matrix; the problems that the FDA-MIMO radar angle-distance decoupling model in the prior art is only suitable for a linear array, and the target parameter estimation method has low estimation accuracy and high calculation complexity can be solved.

A chip-implementation of a millimeter wave MIMO radar comprises transmitters for transmitting short bursts of digitally modulated radar carrier signals and receivers for receiving delayed echoes of those signals. Various signal formats defined by the number of bits per transmit burst, the transmit burst duration, the receive period duration, the bitrate, the number of range bins, and the number of bursts per scan, facilitate the choice of modulating bit patterns such that when correlating for target echoes over an entire scan, the correlation codes for different ranges and different transmitters are mutually orthogonal or nearly so as compared to a random selection of codes. In the event of imperfect orthogonality, the subtraction of strong already-detected target signals allows for better detecting of weaker signals or moving targets that are rendered non-orthogonal by their Doppler shift.