Antenna geometry strategy with prior information for direction-finding MIMO radars

The antenna geometry strategy for direction finding （DF） with multiple-input multiple-output （MIMO） radars is studied. One case, usually encountered is practical applications, is consi- dered. For a directional antenna geometry with a prior direction, the trace-optimal （TO） criterion （minimizing the trace） on the av- erage Cramer-Rao bound （CRB） matrix is employed. A qualitative explanation for antenna geometry is provided, which is a combi- natorial optimization problem. In the numerical example section, it is shown that the antenna geometries, designed by the proposed strategy, outperform the representative DF antenna geometries.

Finite sensor selection algorithm in distributed MIMO radar for joint target tracking and detection

Due to the requirement of anti-interception and the limitation of processing capability of the fusion center, the subarray selection is very important for the distributed multiple-input multiple-output(MIMO) radar system, especially in the hostile environment. In such conditions, an efficient subarray selection strategy is proposed for MIMO radar performing tasks of target tracking and detection. The goal of the proposed strategy is to minimize the worst-case predicted posterior Cramer-Rao lower bound(PCRLB) while maximizing the detection probability for a certain region. It is shown that the subarray selection problem is NP-hard, and a modified particle swarm optimization(MPSO) algorithm is developed as the solution strategy. A large number of simulations verify that the MPSO can provide close performance to the exhaustive search(ES) algorithm. Furthermore, the MPSO has the advantages of simpler structure and lower computational complexity than the multi-start local search algorithm.

Angle estimation in bistatic MIMO radar using improved reduced dimension Capon algorithm

This paper discusses the problem of direction of departure （DOD） and direction of arrival （DOA） estimation for a bistatic multiple input multiple output （MIMO） radar, and proposes an improved reduced-dimension Capon algorithm therein. Compared with the reduced-dimension Capon algorithm which requires pair matching between the two-dimensional angle estimation, the pro- posed algorithm can obtain automatically paired DOD and DOA estimation without debasing the performance of angle estimation in bistatic MIMO radar. Furthermore, the proposed algorithm has a lower complexity than the reduced-dimension Capon algorithm, and it is suitable for non-uniform linear arrays. The complexity of the proposed algorithm is analyzed and the Cramer-Rao bound （CRB） is also derived. Simulation results verify the usefulness of the proposed algorithm.

Angle estimation for bistatic MIMO radar with unknown mutual coupling based on three-way compressive sensing

The problem of angle estimation for bistatic multiple-input multiple-output radar in the present of unknown mutual coupling (MC) is investigated, and a three-way compressive sensing (TWCS) estimation algorithm is developed. To exploit the inherent multi-dimensional structure of received data, a trilinear tensor model is firstly formulated. Then the de-coupling operation is followed. Thereafter, the high-order singular value decomposition is applied to compress the high dimensional tensor to a much smaller one. The estimation of the compressed direction matrices are linked to the compressed trilinear model, and finally two over-complete dictionaries are constructed for angle estimation. Also, Cramer-Rao bounds for angle and MC estimation are derived. The proposed TWCS algorithm is effective from the perspective of estimation accuracy as well as the computational complexity, and it can achieve automatically paired angle estimation. Simulation results show that the proposed method has much better estimation accuracy than the existing algorithms in the low signal-to-noise ratio scenario, and its estimation performance is very close to the parallel factor analysis (PARAFAC) algorithm at the high SNR regions. ? 2017 Beijing Institute of Aerospace Information.

Polyphase coded signal design for MIMO radar using MO-MicPSO

A novel modified optimization technique known as the multi-objective micro particle swarm optimization（MO-MicPSO） is proposed for polyphase coded signal design.The proposed MO-MicPSO requires only a small population size compared with the standard particle swarm optimization that uses a larger population size.This new method is guided by an elite archive to finish the multi-objective optimization.The orthogonal polyphase coded signal（OPCS） can fundamentally improve the multiple input multiple output（MIMO） radar system performance,with which the radar system has high resolution and abundant signal channels.Simulation results on the polyphase coded signal design show that the MO-MicPSO can perform quite well for this high-dimensional multi-objective optimized problem.Compared with particle swarm optimization or genetic algorithm,the proposed MO-MicPSO has a better optimized efficiency and less time consumption.

Tracking multiple targets in MIMO radar via adaptive asymmetric joint diagonalization with deflation

In view of the low performance of adaptive asymmetric joint diagonalization（AAJD）, especially its failure in tracking high maneuvering targets, an adaptive asymmetric joint diagonalization with deflation（AAJDd） algorithm is proposed. The AAJDd algorithm improves performance by estimating the direction of departure（DOD） and direction of arrival（DOA） directly, avoiding the reuse of the previous moment information in the AAJD algorithm.On this basis, the idea of sequential estimation of the principal component is introduced to turn the matrix operation into a constant operation, reducing the amount of computation and speeding up the convergence. Meanwhile, the eigenvalue is obtained, which can be used to estimate the number of targets. Then, the estimation of signal parameters via rotational invariance technique（ESPRIT） algorithm is improved to realize the automatic matching and association of DOD and DOA. The simulation results show that the AAJDd algorithm has higher tracking performance than the AAJD algorithm, especially when the high maneuvering target is tracked. The efficiency of the proposed method is verified.

Detection of weak target for MIMO radar based on Hough transform

An effective method of multiple input multiple output （MIMO） radar weak target detection is proposed based on the Hough transform. The detection time duration is divided into multiple coherent processing intervals （CPIs）. Within each CPI, conventional methods such as fast Fourier transform （FFT） is exploit to coherent inte- grating in same range cell. Furthermore, noncoherent integration through several range cells can be implemented by Hough transform among all CPIs. Thus, higher integration gain can be obtained. Simulation results are also given to demonstrate that the detection performance of weak moving target can be dramatically improved.

Fast multi-parameter estimation and localization for MIMO radar

This paper addresses the problem of four-dimensional angle and Doppler frequency estimation for bistatic multiple-input multiple-output （MIMO） radar with arbitrary arrays in spatial co- lored noise. A novel method for joint estimation of Doppler fre- quency, two-dimensional （2D） direction of departure and 2D direc- tion of arrival based on the propagator method （PM） for arbitrary arrays is discussed. A special matrix is constructed to eliminate the influence of spatial colored noise. The four-dimensional （4D） angle and Doppler frequency are extracted from the matrix and the three- dimensional （3D） coordinates of the targets are then calculated on the basis of these angles. The proposed algorithm provides a lower computational complexity and has a parameter estimation very close to that of the ESPRIT algorithm and the DOA-matrix al- gorithm in the high signal to noise ratio and the Cramer-Rao bound （CRB） is given. Furthermore, multi-dimensional parameters can be automatically paired by this algorithm to avoid performance degra- dation resulting from wrong pairing. Simulation results demonstrate the effectiveness of the proposed method.

Adaptive detector design of MIMO radar with unknown covariance matrix

The problem of detecting signal with multiple input mul-tiple output （MIMO） radar in correlated Gaussian clutter dominated scenario with unknown covariance matrix is dealt with. The gen-eral MIMO model, with widely separated sub-arrays and co-located antennas at each sub-array, is adopted. Firstly, the generalized likelihood ratio test （GLRT） with known covariance matrix is ob-tained, and then the Rao and Wald detectors are devised, which have proved that the Rao and Wald test coincide with GLRT detec-tor. To make the detectors fully adaptive, the secondary data with signal-free will be collected to estimate the covariance. The per-formance of the proposed detector is analyzed, however, it is just ancillary. A thorough performance assessment by several numer-ical examples is also given, which has considered the sense with co-located antennas configure of transmitters and receivers array. The results show that the performance the proposed adaptive de-tector is better than LJ-GLRT, and the loss can be acceptable in comparison to their non-adaptive counterparts.

Cramer-Rao bound of joint estimation of target location and velocity for coherent MIMO radar

The optimal estimation performance of target parameters is studied. First, the general form of Cramer-Rao bound （CRB） for joint estimation of target location and velocity is derived for coherent multiple input multiple output （MIMO） radars. To gain some insight into the behavior of the CRB, the CRB with a set of given orthogonal waveforms is studied as a specific case. Second, a maximum likelihood （ML） estimation algorithm is proposed. The mean square error （MSE） of the ML estimation of target location and velocity is obtained by Monte Carlo simulation and it approaches CRB in the high signal-to-noise ratio （SNR） region.

Modulation recognition of MIMO radar signal based on joint HOS and SNR algorithm

This paper presents a joint high order statistics （HOS） and signal-to-noise ratio （SNR） algorithm for the recognition of multiple-input multiple-output （MIMO） radar signal without a priori knowledge of the signal parameters. This method is capable of recognizing the MIMO radar signal as well as discriminating it from single-carrier signal adopted by conventional radar. Meanwhile, the sub-carrier number of the none-coding MIMO radar signal is estimated. Extensive simulations are carried out in different operating conditions. Simulation results prove the feasibility and indicate that the recognition probability could reach over 90% when the value of SNR is above 0 dB.

Multi-target localization for bistatic MIMO radar in the presence of unknown mutual coupling

A decoupling-estimation signal parameters via rotarional invariance technique（ESPRIT） method is presented for multi-target localization with unknown mutual coupling in bistatic multiple-input multiple-output（MIMO） radar.Two steps are carried out in this method.The decoupling operation between angle and mutual coupling estimates is realized by choosing the auxiliary elements on both sides of the transmit and receive uniform linear arrays（ULAs）.Then the ESPRIT method is resilient against the unknown mutual coupling matrix（MCM） and can be directly utilized to estimate the direction of departure（DOD） and the direction of arrival（DOA）.Moreover,the mutual coupling coefficient is estimated by finding the solution of the linear constrained optimization problem.The proposed method allows an efficient DOD and DOA estimates with automatic pairing.Simulation results are presented to verify the effectiveness of the proposed method.

Antenna selection in MIMO radar with collocated antennas

An antenna adjustment strategy is developed for the target tracking problem in the collocated multiple-input multipleoutput(MIMO)radar.The basic technique of this strategy is to optimally allocate antennas by the prior information in the tracking recursive period,with the objective of enhancing the worst-case estimate precision of multiple targets.On account of the posterior Cramer-Rao lower bound(PCRLB)offering a quantitative measure for target tracking accuracy,the PCRLB of joint direction-of-arrival(DOA)and Doppler is derived and utilized as the optimization criterion.It is shown that the dynamic antenna selection problem is NP-hard,and an efficient technique which combines convex relaxation with local search is put forward as the solution.Simulation results demonstrate the outperformance of the proposed strategy to the fixed antenna configuration and heuristic search algorithm.Moreover,it is able to offer close-to performance of the exhaustive search method.

Adaptive time-space resource and waveform control for collocated MIMO radar with simultaneous multi-beam

Collocated multiple input multiple output(MIMO)radar,which has agile multi-beam working mode,can offer enhanced multiple targets tracking(MTT)ability.In detail,it can illuminate different targets simultaneously with multi-beam or one wide beam among multi-beam,providing greater degree of freedom in system resource control.An adaptive time-space resource and waveform control optimization model for the collocated MIMO radar with simultaneous multi-beam is proposed in this paper.The aim of the proposed scheme is to improve the overall tracking accuracy and meanwhile minimize the resource consumption under the guarantee of effective targets detection.A resource and waveform control algorithm which integrates the genetic algorithm(GA)is proposed to solve the optimization problem.The optimal transmitting waveform parameters,system sampling period,sub-array number,binary radar tracking parameterχ_i(t_k),transmitting energy and multi-beam direction vector combination are chosen adaptively,where the first one realizes the waveform control and the latter five realize the timespace resource allocation.Simulation results demonstrate the effectiveness of the proposed control method.

MIMO radar dwell scheduling based on novel pulse interleaving technique

According to the signal processing characteristic of MIMO radars,an adaptive dwell scheduling algorithm is proposed.It is based on a novel pulse interleaving technique,which makes full use of transmitting,waiting and receiving durations of radar dwells.The utilization of transmitting duration is unique for MIMO radars and is realized through transmitting duration overlapping.Simulation results show that,compared with the conventional scheduling algorithm,the scheduling performance of MIMO radars can be improved effectively by the proposed algorithm,and the scheduling rule can be chosen arbitrarily when using the proposed algorithm.

Extended ambiguity function for bistatic MIMO radar

This paper derives the extended ambiguity function for a bistatic multiple-input multiple-output （MIMO） radar system, which includes the whole radar system parameters： geometric sensor configuration, waveforms, range, range rate, target scattering and noise characteristics. Recent research indicates the potential pa- rameter estimate performance of bistatic MIMO radars. And this ambiguity function can be used to analyze the parameter estimate performance for the relationship with the Cramer-Rao bounds of the estimated parameters. Finally, some examples are given to demonstrate the good parameter estimate performance of the bistatic MIMO radar, using the quasi-orthogonal waveforms based on Lorenz chaotic systems.

Target estimation using MIMO radar with multiple subcarriers

This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. How the number of subcarriers in- fluences the estimation accuracy is illustrated by considering the joint Cramer-Rao bound and the mean square error of the maxi- mum likelihood estimate. The non-coherent MIMO radar ambiguity function with multiple subcarriers is developed and investigated by changing the number of subcarriers, the pulse width and the frequency spacing between adjacent subcarriers. The numerical results show that more subcarriers mean more accurate estimates, higher localization resolution, and larger pulse width results in a worse performance of target location estimation, while the fre- quency spacing affects target location estimation little.

MIMO Radar Waveform Design:An Overview

Waveform or code design is an important topic in many applications,which has continuously attracted attention during the past several decades.The development of waveform design has been significantly advanced since the emergence of multiple-input multiple-output(MIMO)technique.Compared to the single-waveform design for conventional radars,the multi-waveform design enables extra degrees of freedom(DOFs)for modern radars,which therefore triggers a series of relevant studies on MIMO radar.In this paper,we provide an overview on the main techniques of MIMO radar waveform designs developed in recent years,wherein the state-of-the-art methods are reviewed in terms of different designing criteria,including the minimization of auto-and cross-correlation levels(or equivalently,the integrated sidelobe level),the information theoretic,ambiguity function shaping,and signal-to-interference-plus-noise ratio maximization-based criteria,etc.Moreover,we give detailed comments on the main issues of different waveform designs,and also provide the possibly emerging directions toward the research on MIMO radar waveform design and potential challenges.

Modified OMP method for multi-target parameter estimation in frequency-agile distributed MIMO radar

Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target parameter estimation.Sparse recovery is an effective way to address this problem,but it cannot be directly utilized for multi-target parameter estimation in frequency-agile distributed MIMO radars due to spatial diversity.In this paper,we propose an algorithm for multi-target parameter estimation according to the signal model of frequency-agile distributed MIMO radars,by modifying the orthogonal matching pursuit(OMP)algorithm.The effectiveness of the proposed method is then verified by simulation results.

Joint resource allocation scheme for target tracking in distributed MIMO radar systems

A joint resource allocation scheme concerned with the sensor subset,power and bandwidth for range-only target tracking in multiple-input multiple-output(MIMO)radar systems is proposed.By selecting an optimal subset of sensors with the predetermined size and implementing the power allocation and bandwidth strategies among them,this algorithm can help achieving a better performance within the same resource constraints.Firstly,the Bayesian Cramer-Rao bound(BCRB)is derived from it.Secondly,a criterion for minimizing the BCRB at the target location among all targets tracking in a certain range is derived.Thirdly,the optimization problem involved with three variable vectors is formulated,which can be simplified by deriving the relationship between the optimal power allocation vector and the bandwidth allocation vector.Then,the simplified optimization problem is solved by the cyclic minimization algorithm incorporated with the sequential parametric convex approximation(SPCA)algorithm.Finally,the validity of the proposed method is demonstrated with simulation results.