818 results about "Mimo radar" patented technology

This invention is related to a deep multi-sensor fusion system for inter-radar interference-free environmental perception comprising of (1) polystatic Multi-Input Multi-Output (MIMO) radars such as radio frequency radar and laser radar; (2) vehicle self-localization and navigation; (3) the Internet of Vehicles (IoV) including Vehicle-to-Vehicle communication (V2V), Vehicle-to-Infrastructure communication (V2I), other communication systems, data center / cloud; (4) passive sensors such as EOIR, and (5) deep multi-sensor fusion algorithms. The self-localization sensors and V2X formulate cooperative sensors. The polystatic MIMO radar on each vehicle utilizes both its own transmitted radar signals and ones from other vehicles to detect obstacles. The transmitted radar signals from other vehicles are not considered as interference or uselessness as conventional radars, but considered as useful signals to formulate a polystatic MIMO radar which can overcome the interference problem and improve the radar performance. This invention can be applied to all kinds of vehicles and robotics.

A radar system has different modes of operation. In one mode the radar operates as a single-input, multiple-output (SIMO) radar system utilizing one transmitted signal from one antenna at a time. Codes with known excellent autocorrelation properties are utilized in this mode. At each receiver the response after correlating with various possible transmitted signals is measured in order to estimate the interference that each transmitter will represent at each receiver. The estimated effect of the interference from one transmitter on a receiver that correlates with a different code is used to mitigate the interference. In another mode, the radar operates as a MIMO radar system utilizing all the antennas at a time. Interference cancellation of the non-ideal cross correlation sidelobes when transmitting in the MIMO mode are employed to remove ghost targets due to unwanted sidelobes.

A method and apparatus for enhanced microwave imaging of an object collects microwave responses for multiple combinations of transmit antennas, receive antennas, and object movement states. The responses are grouped into sets of responses corresponding to at least two object movement states. An image is reconstructed from the set of responses for each movement state, and a differential image representative of object movement is generated from the reconstructed image for each of the at least two object movement states. The differential image is overlaid on a reconstructed image to obtain an enhanced composite image of the object.

The invention discloses a method for estimating target arrival angle of a multiple input multiple output (MIMO) radar, which mainly solves the problem of large signal processing capacity in the target positioning process of MIMI radar. The method comprises the following steps of: 1) obtaining a virtual array of echo of each receiving antenna by a matched filter bank; 2) constructing a data conversion matrix and a dimension reduction array according to position of transmitting and receiving array; (3) reducing dimension of the virtual array data by the dimension reduction array to obtain an effective array after dimension reduction; 4) constructing two sub-arrays by rotational variance of effective array, and deriving covariance matrix of data; 5) decomposing eigenvalue of covariance matrix to obtain signal sub-spaces corresponding to two sub-arrays; 6) deriving rotational invariant relationship matrix by least square method to obtain arrival angle of target. The dimension reduction matrix form constructed by the method has versatility; the computation quantity is reduced by the dimension reduction of data and the ESPRIT (estimating signal parameter via rotational invariance techniques) algorithm; the computation speed of MIMO radar is increased; and the real-time signal processing of the MIMO radar is made easier.

The invention discloses a bilateral constraint self-adaptive wavebeam forming method for a multiple-input-multiple-output (MIMO) radar, which can constrain both transmitting signals and receiving signals. Firstly, a plurality of transmitting signal data can be recorded, and the corresponding echo signals can be sampled, all vectors which are obtained by the recorded transmitting signal data and the sampled echo signals are respectively ranked by row to form a data matrix, and an optimal weight vector required for forming the wavebeam is calculated by the dual iterative calculation method, finally, the calculated optimal weight can be used to form the wavebeam. The method can overcome the shortcomings of large sample number and complex calculation in traditional self-adaptive wavebeam-forming method which is applied to the MIMO radar. Compared with the traditional self-adaptive wavebeam-forming method, the obtained antenna array pattern is provided with lower side lobe and better wavebeam shape preserving ability. The performance by using the method to perform Doppler frequency detection for movable object after the received MIMO radar data is filtered in spatial field also exceeds that of the traditional self-adaptive wavebeam-forming method.

A method and apparatus for enhanced microwave imaging of an object collects microwave responses for multiple combinations of transmit antennas, receive antennas, and object movement states. The responses are grouped into sets of responses corresponding to at least two object movement states. An image is reconstructed from the set of responses for each movement state, and a differential image representative of object movement is generated from the reconstructed image for each of the at least two object movement states. The differential image is overlaid on a reconstructed image to obtain an enhanced composite image of the object.

The invention discloses a multiple input multiple output (MIMO) radar array position error self-correcting method based on a genetic algorithm, belonging to an MIMO radar array position error self-correcting method. The method comprises the following steps of: carrying out one-dimensional spectral peak search according to an ideal array element position by utilizing a MUSIC method to obtain the initial value theta k of direction of arrival (DOA); generating an initial group, carrying out individual fitness evaluation according to f(G), and finding out f max; carrying out genetic evolution operations of selection, crossing, heteromorphosis and the like to generate a new generation of search group, and carrying out fitness evaluation to reduce a deviation factor sigma; revising the theta k according to the optimal individual in the population; and carrying out genetic iteration until a greatest iteration number is set. By using the method, online estimation and correction of array position error can be finished while the DOA estimation is carried out, thereby the robustness of estimation of system parameters is improved.

The invention discloses a method for estimating the DOA and DOD of an MIMO radar based on a co-prime array, and mainly solves problems in the prior art that an MIMO radar system is low in accuracy of target detection and is small in number of recognizable information sources. The method comprises the following steps: (1) building a co-prime array model; (2) obtaining array receiving data; (3) calculating an array receiving vector; (4) estimating a covariance matrix; (5) drawing an MUSIC power spectrum chart, and estimating DOA and DOD values. The method provided by the invention remarkably improves the accuracy of target detection and increases the number of recognizable information sources. The method can be used for the detection of passive positioning of an airplane, a ship or other moving objects through a radar.

A MIMO radar device for the decoupled determination of an elevation angle and azimuth angle of an object. The MIMO radar device includes an antenna array including multiple transmitting antennas, whose phase centers are situated spaced apart from one another along a first coordinate direction; and multiple receiving antennas, whose phase centers are situated spaced apart from one another along the first coordinate direction; the phase center of at least one of the transmitting antennas being spaced apart from the phase centers of the remaining transmitting antennas by an offset value along a second coordinate direction; the phase center of at least one of the receiving antennas being spaced apart from the phase centers of the remaining transmitting antennas by the offset value along the second coordinate direction; an evaluation unit to evaluate electromagnetic signals for the decoupled determination of the elevation angle and the azimuth angle of the object.

A Multiple Input Multiple Output (MIMO) radar system and method of using it for target recovery are disclosed. The MIMO radar system comprises an array of distributed radiating elements configured to transmit signals towards a target scene, an array of distributed receiving elements configured to receive signals backscattered from the target scene, a sampling module configured to sample the signals received, and a hardware processor configured to recover from the samples position parameters of one or more targets. Range, direction and optionally velocity, are estimated via simultaneous 2D or 3D sparse matrix recovery, wherein all channels defined by transmitter-receiver pairs are processed together. The digital processing may be applied either in Nyquist or sub-Nyquist scheme, reducing the number of samples, transmit and / or receive antennas. The radar system is optionally further enhanced by cognitive transmission scheme where transmitted signals are distributed over a wide frequency range with vacancy bands left therein.

In a method for operating a MIMO radar, an influence of an object motion on an angle estimate is substantially eliminated, and a time multiplex schema having a transmission sequence and transmission instants of transmitters of the MIMO radar is identified by optimizing the following mathematical relationship: d _ pulses , opt = arg max d _ pulses [ Var S ( d _ pulses ) - ( Cov S ( d _ pulses , t ) ) 2 / Var S ( t _ ) ] in which: dpulses,opt is optimized positions of the transmitters in the sequence in which they transmit; dpulses is positions of the transmitters in the sequence in which they transmit; t is transmission instants; VarS is sample variance; and CovS is sample covariance.

This invention is related to a cognitive Multi-Input Multi-Output (MIMO) radio frequency (or laser) radar with large-area synchronized multi-dimensional hopping spread spectrum and Interference-Free Windows (IFWs) for autonomous vehicles comprising of (1) analog component; (2) digital baseband component; (3) multi-dimensional hopping code generator; (4) large-area time synchronization; (5) cooperative IFW; and (6) cognitive engine. The new MIMO radar can provide interference-free environmental perception intelligently by the multi-dimensional IFWs formulated by beat-frequency hopping, beat-time hopping, discrete sequence (DS), cooperative IFW, array processing, and image denoising and fusion, etc. This invention increases the frequency efficiency greatly, and be applied to autonomous vehicles and robotics under sparse, dense, mixed autonomous and human driving, or completely autonomous driving environments.

The invention relates to a low-sidelobe emission directional diagram design method improving DOA estimated performance of a MIMO radar. The method comprises the following steps: setting an interesting area; ensuring column vectors of a beam space weighting matrix to satisfy pairing characteristics; ensuring signals at a receiving end to satisfy rotation invariance; constructing an optimized model of a beam space weighting matrix with directional diagram coupling characteristics, rotation invariance of the signals and equality of various array element emission powers as constraint conditions; introducing an auxiliary variable and relaxing a rank-1 constraint to be a positive semidefinite constraint through utilization of the semidefinite relaxing technology; and through utilization of an interior point method, obtaining an optimal solution of the relaxing problem; through a Gaussian randomization method, the beam space weighting matrix is solved; and DOA estimation is carried out on a target at the receiving end through the ESPRIT algorithm. The MIMO radar waveform design technology which is good in performance in the invention can raise the signal to noise ratio at the receiving end, provide an important theoretical basis and a specific realization method for raising the precision of MIMO radar angle estimation.

A method for obtaining an adaptive angle-Doppler ambiguity function (AF) for a target using multiple-input-multiple-output (MIMO) radar that includes a transmit antenna array having a plurality of antenna elements. The method includes generating transmit signals for transmission by the transmit antenna array, the transmit signals defining at least a first transmit trajectory of a phase center within the transmit antenna array; transmitting the transmit signals using the transmit antenna array and receiving receive signals from the target, the receive signals resulting from the incidence of the transmit signals upon the target; and obtaining at least an angle-Doppler ambiguity function (AF) from the receive signals. The first transmit trajectory is such that, in operation, the phase center undergoes random phase center motion (PCM), such that a phase center position within the transmit antenna array varies randomly with time. A system for obtaining an AF is also disclosed.

The invention provides an integral coding / decoding method based on MIMO radar communication. The orthogonal spread spectrum code sequence guarantees the orthogonality of bipolar phase spread spectrum code sequence based on WalsH matrix. The requirement of the radar to the detection of signal self-correlation peak value, mutual correlation peak value low side-lobe can be satisfied through the genetic algorithm. The signal encoding is based on soft spread spectrum biorthogonal encoding. To satisfy the requirement of the MIMO radar to detection signal, different spreading coding sequences can be used on different encode element positions; special sending channel can be reserved as the time and frequency synchronous standard, the first encode element position of each sending channel is reserved as the phase position standard, and special synchronous spreading codes are used on the positions. According to the method provided by the invention, conventional carrier frequency offset extraction technology, carrier phase partial extraction technology and soft spread spectrum biorthogonal decoding method are improved specifically according to the requirement of the radar / radio frequency integrate realization, accompanied by the frequency offset tracking technology with Alpha -Beta as the core, accuracy of data deviation correction is guaranteed.

A MIMO FMCW radar sensor and a MIMO time multiplexing method for localizing a radar target, in which an FMCW radar measurement is performed with a transmitted signal whose modulation pattern encompasses, for different transmission switching states that differ in terms of the selection of antenna elements used for transmission, mutually temporally interleaved sequences of ramps; ambiguous values for the relative velocity of the radar target are determined from a position of a peak in a two-dimensional spectrum; phase relationships between spectral values of spectra are checked for agreement with phase relationships expected for several of the determined values of the relative velocity; on the basis thereof, an estimated value for the relative velocity of the radar target is selected from the determined periodic values of the relative velocity; and the angle of the radar target is determined on the basis of amplitudes and / or phase relationships between obtained baseband signals.

The invention discloses a method for designing MIMO radar waveforms. The method mainly solves the problem in the prior art that tolerance of Doppler is poor in the process of waveform design. The implementation steps of the method include the first step of fixing a set of waveform center frequency sequences of a radar and setting an initial phase to be zero, the second step of searching a frequency interval initial variable to find out a frequency interval initial value which satisfies the requirement that the 3dB bandwidth of an emitted energy function equals to the 3dB bandwidth of an ideal emitted energy function, the third step of setting a frequency interval according to the frequency interval initial value, the fourth step of inputting the frequency interval and the initial phase and outputting an emitted energy function difference value, emitting direction sidelobe gain and the sidelobe magnitude of signals after pulse synthesis to construct a cost function, the fifth step of calling the cost function and optimizing the cost function through the minimax method to obtain the frequency interval and the initial phase meeting the requirement, and the sixth step of obtaining a set of final signals according to the frequency interval and the initial phase and completing the design of the waveforms. The waveforms designed through the method have the advantages of being good in the tolerance of the Doppler and applicable to target detection.

The invention discloses an iterative least square method-based MIMO (multiple input multiple output) radar DOA (direction-of-arrival) estimation method, which is characterized in that receiving and transmitting array response matrixes on which dimension-reduced processing is performed are solved by using an iterative least square method. The iterative least square method-based MIMO radar DOA estimation method comprises the following steps: firstly, performing the dimension-reduced processing on echo data matrixes of multiple radar transmitted pulses and the receiving and transmitting array response matrixes; then, establishing cost functions under the least square condition, and solving the cost functions by utilizing a gradient descent-based iterative method; finally, estimating the direction of a target by utilizing known receiving and transmitting array manifolds. Compared with a traditional monostatic MIMO radar array DOA estimation method, the iterative least square method-based MIMO radar DOA estimation method disclosed by the invention directly obtains the DOA estimation of the target, and does not need to perform spectrum peak search. Noise is effectively suppressed by adopting the dimension-reduced processing, and the estimation accuracy under low signal to noise ratio is improved; the estimation, the inversion and the eigenvalue decomposition operation of high-dimensional data covariance matrixes are avoided; the defects that the calculated amount is high and the needed sample number is large when the traditional array DOA estimation method is applied to a monostatic MIMO radar are overcome.

The invention discloses a microwave photon MIMO radar detection method comprising modulating M intermediate-frequency linear frequency-modulated signals with the same bandwidth and chirp rate and non-overlapped frequency on M optical carriers with different wavelengths to generate M optical signals where only the positive and negative second-order sidebands are retained; merging the M optical signals by an optical wavelength division multiplexer and then dividing a combined optical signal into two channels; dividing the optical signal in one channel into N reference light beams; subjecting theoptical signal in the other channel to photoelectric conversion and separating and transmitting M orthogonal linear frequency-modulated signals therein; receiving, by N receiving antennas, the targetreflected signals, performing de-chirp processing and wavelength demultiplexing, and subjecting the obtained M optical signals to photoelectric conversion, low-pass filtering and analog-to-digital conversion to obtain M*N digital signals, processing the digital signals to obtain a target detection result. The invention also discloses a microwave photon MIMO radar system. The method can greatly improve the range resolution and azimuth resolution of the radar system.

The invention relates to a distributed MIMO radar target tracking accuracy joint resource optimization method. The method includes the following steps that: an objective function is derived, a resource allocation optimization model containing three variables, namely, array element, power and bandwidth is constructed; the model is simplified, an array element selection problem is converted into a convex optimization problem from a 0-1 problem through convex relaxation; and the optimization model is decomposed into iterative optimization sub-problems of array element selection and power allocation through using cyclic minimization, the problems are solved through using an SPCA (sequential parametric convex approximation) method until the objective function is not optimized any more, final array element selection and power allocation results are obtained, and a final bandwidth allocation result is calculated, and a target position at a next time point is estimated. According to the distributed MIMO radar target tracking accuracy joint resource optimization method of the invention, the accuracy of the target tracking of an MIMO radar can be effectively improved through resource allocation, and the utilization rate of resources can be also improved; and an appropriate array element subset is selected, and power and bandwidth resources are allocated optimally, and therefore, the accuracy of the target tracking can be further improved under a situation that radar system resources are limited.

The invention discloses a method for united correction of MIMO radar transceiving array errors, wherein the method can improve array error correction precision. Echo signals of an antenna array are obtained, the echo signals are utilized to construct a receiving array covariance matrix and a transmitting array covariance matrix, the covariance matrixes of both a receiving array and a transmitting array are utilized to respectively correct the received and transmitted array errors, angular measurement inaccuracy caused by array errors is avoided, and the array errors of the receiving array and the transmitting array can be simultaneously corrected; orientation dependence occurs in an array guiding vector due to the array errors in collection, the antenna array rotates through J angles by enabling the antenna array comprising M array elements to be arranged on a turntable, the echo signals of the antenna array at each angle are respectively received, sample data of plenty of orientation angles of a plurality of orientations can be collected, and array error correction precision is improved. The method is suitable for being popularized and applied in the field of array signal processing.

A multiple-input-multiple-output radar waveform design method belongs to the radar communication technical field, and aims to provide a design method with lower related sidelobe and frequency spectrum inhibition depth, high efficiency, less consumption, high robustness, and excellent time frequency anti-interference performance; the method comprises the following steps: pre-evaluating an autocorrelation sidelobe inhibition fuzzy region according to a relative position between a strong scatterer and a to be measured object in a radar scene, thus forming a corresponding object function; analyzing MIMO radar waveform orthogonality constraint so as to form the object function satisfying the orthogonality constraint; pre-evaluating a frequency domain interference fuzzy frequency band zone according to scene prior information, thus forming the corresponding object function; forming a constant modulus phase coding waveform constrained condition; forming a loose alternative projection algorithm framework; solving a waveform design according to the loose alternative projection algorithm framework, thus providing three waveform optimization output modes. The loose alternative projection constant modulus waveform coding design enables the MIMO radar to have batter detection performance.

The invention relates to a multi-parameter combined estimation method based on bi-static FDA-MIMO radars. The method comprises the following steps: firstly designing a transmitting signal by utilizing characteristics of FDA and MIMO radars; carrying out matched filtering, vectorization and spatial smooth processing on a receiving signal; then estimating a combined steering vector and estimating a DOA and a speed parameter by utilizing an ESPRIT algorithm, and carrying out decoupling and parameter estimation on the DOD and distance information by combining characteristics of a transmitting waveform; and carrying out ambiguity resolution on a distance result estimated by utilizing an ESPRIT algorithm and combining a distance estimated by virtue of a pulse delay estimation algorithm, and carrying out ambiguity resolution on a speed by virtue of an MUSIC algorithm by combining signal characteristics of a large number of pulses. The method provided by the invention has the advantages that the problem that the distance and speed can not be accurately estimated under the condition of a single PRF can be effectively solved, and the estimation of the three-dimensional position and speed of a target can be realized; and a simulation result shows that the method provided by the invention has good estimation accuracy and stability.

The invention discloses a method for estimating target direction by a multiple input multiple output (MIMO) radar, belonging to the technical field of radars and mainly solving the problem of limiting computation complexity, computation speed and estimation precision in the prior art. The method comprises the steps of: firstly, carrying out the distance compression on a radar echo signal; secondly, carrying out reduction of dimensionality on the compressed echo signal; thirdly, constructing a cost function to the echo signal subjected to the reduction of dimensionality according to the least squares criterion and solving by using a three-iterative approach; and fourthly, computing a direction-of-arrival angle of a target through computing a receiving and sending guide vector matrix by using an array popularity of a receiving array and a sending array. The invention has the advantages of low computation complexity, high computation speed and high estimation precision, and can be used for estimating the direction-of-arrival angle of the target of the MIMO radar.

A Pseudo-Random Phase Modulation (PRPM) multiple-input-multiple-output (MIMO) radar system suitable for use on an automated vehicle includes a first transmit-antenna that transmits a first transmit-signal generated by a first PRPM-code, a second transmit-antenna that transmits a second transmit-signal generated by a second PRPM-code, a receive-antenna used to detect a first reflected-signal arising from the first transmit-signal and a second reflected-signal arising from the second transmit-signal, and a controller. The controller is in communication with the receive-antenna and is operable to generate the first PRPM-code and the second PRPM-code. The controller is configured to generate a first sub-channel-output based on a down-converted-signal from the receive-antenna and the first PRPM-code, generate a second sub-channel-output based on the down-converted-signal from the receive-antenna and the second PRPM-code, determine a first residue-signal based on the second sub-channel-output, and determine a first residue-removed-signal by subtracting the first residue-signal from the first sub-channel-output.

The invention discloses a waveform optimized design method for a frequency controlled array MIMO radar system, aiming to solve the problem that too much test data is to be processed for obtaining distance, angle, and resolution of high dimension Doppler. The implementation process is: 1) according to the target environment requirement, determining the transmitting carrier frequency, frequency increment, antenna quantity, and waveform code element length of the frequency controlled array MIMO radar; 2) according to a received data model, constructing decoupling between transmitted waveforms and virtual steering vectors; 3) according to a constructed data matrix, determining the coherence of the data matrix; 4) according to the coherent characteristics of matrix completion, designing transmitting waveform of the frequency controlled array MIMO radar by use of optimized method. By use of the method, through the transmitting waveform design for the frequency controlled array MIMO radar, the coherence of the received data is made as low as possible. Therefore, the method has an advantage that smaller data quantity is needed when accurate target detection and estimation are obtained; the method can be applied in frequency controlled array MIMO radar waveform design.

The invention discloses a local-area joint-dimension-reduction range ambiguity clutter suppression method based on an FDA-MIMO radar so that problems that the existing range ambiguity clutter suppression method has the poor detection performance, the operation load is high, and the requirement on the independent and identically distributed samples is high can be solved. The method comprises: stepone, carrying out matching and filtering on echo data of a radar by using a transmitting waveform; step two, carrying out range dependence compensation on the matched filtered data; step three, constructing a local-area joint dimension reduction matrix and performing dimension reduction on the received data; step three, on the basis of data after dimension reduction, estimating a clutter covariance matrix; step four, on the basis of a minimum variance, non-distortion response to a wave beam forming device is carried out to obtain an optimal weight vector; step five, carrying out weighting on the data after dimension reduction by using an optimal weight, suppressing a range ambiguity clutter, and detecting a target signal. Compared with the existing range ambiguity clutter suppression method, the provided method has the following advantages: the computing complexity is low; the requirement on the independent and identically distributed samples is low; and the clutter suppression performance is good. The range ambiguity clutter suppression on an airborne radar is realized. The method can be applied to ground moving target detection of an airborne radar.

The invention provides a method for designing a loop-optimization-based emission beam matrix in a FDA-MIMO radar. The method is characterized in that the feature that when a small frequency increment is added to a frequency control matrix through adjacent matrix elements, emission beams with angles and distance dependence can be produced, and possibility is provided for the angle and distance parameter combined positioning of a target is utilized to combine with the frequency control matrix and an MIMO radar, and combined estimation of the distances and angles of multiple targets is achieved by optimally designing the emission beam matrix. The method specifically includes: determining emission carrier waves, the frequency increment and emission receiving antenna number according to actual needs and the features of a frequency control matrix MIMO radar system, and building a frequency control matrix MIMO radar system model; using a loop optimization method to design the emission beam matrix of the radar; verifying the performance of estimated distances, angles and amplitudes on the basis of the emission beam matrix. The method is essentially a method minimizing the mutual coherence principle of a perception matrix in a thinning model to increase distance and angle-dimension resolution.

The invention discloses a receiving-transmitting type robust dimensionality-reducing self-adaptive beam forming method of coherent MIMO (Multiple Input Multiple Output) radar. The receiving-transmitting type robust dimensionality-reducing self-adaptive beam forming method comprises the following steps: firstly, separating a transmitting-receiving two-dimensional weight vector in the coherent MIMO radar into a transmitting weight vector and a receiving weight vector to realize dimensionality reduction; then utilizing a two-order convex optimization algorithm to deduce a double-secondary cost function and a constraint condition based on a bilateral guiding vector error model; calculating an optimal weight vector needed by beam forming by using a double iteration method; and finally, robustly realizing self-adaptive beam forming by using the optimal weight vector. According to the receiving-transmitting type robust dimensionality-reducing self-adaptive beam forming method, the disadvantages that a very great sample quantity and a great calculation quantity are needed when a traditional self-adaptive beam forming method is applied to the coherent MIMO radar are overcome. Compared with the traditional self-adaptive beam forming method, the needed sample quantity and calculation quantity are reduced to the great extent, the convergence speed is improved greatly and the robustness is very good.