Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning

This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.

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.

ANALYSIS OF TRANSMIT BEAMFORMING PERFORMANCE ON MULTIPLE-TRANSMIT BINARY ZCZ WAVEFORMS

The Transmit BeamForming (TBF) technology, applied in a multiple-transmit radar system, is studied in this paper, where multiple elements of antenna array transmit binary Zero Correlation Zones Orthogonal Signals (ZCZ-OS) independently. For each Direction Of Arrival (DOA) with respect to the transmitting array, the analysis on the gain and sidelobe level of TBF output is presented. This paper focuses on the range sidelobes performance within the main beam (in angle domain). For the normal direction, due to the inherent phase property of ZCZ-OS, the TBF output has part zero sidelobes area, of which the distribution is discussed. For the other directions, a systematic search algorithm to optimize the transmission order of signals is proposed for an optimal relationship chart of DOA and transmission order. The range sidelobe performance within the main beam can be improved as the optimal transmission order is adopted.

Design of integrated radar and communication system based on MIMO-OFDM waveform

Orthogonal frequency division multiplexing (OFDM) waveform enables radar and communication functions simultaneously, which encounters low angle resolution and poor data rate for traditional single input single output (SISO) systems. To solve these problems, an integrated radar and communication system (IRCS) with multiple input multiple output (MIMO) OFDM waveform is proposed. The different limitations of radar and communication in designing such a system are investigated. Then, an optimization problem is devised to obtain suitable system parameters, including the number of subcarriers, subcarrier spacing, number of symbols, pulse repetition frequency (PRF) and length of cyclic prefix (CP). Finally, to satisfy the requirements of both radar and communication, the IRCS parameters are derived in three typical cases. Several numerical results are presented to illustrate the demands of radar and communication, inconsistent or consistent, for the IRCS parameters and the superiority of the proposed system.

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.

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.

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.

ORTHOGONAL DISCRETE FREQUENCY-CODING WAVEFORM DESIGN FOR MIMO RADAR

Design of orthogonal code sets with ideal correlation properties is crucial for orthogonalMultiple Input Multiple Output(MIMO)radar.A modified Genetic Algorithm(GA)is proposed tonumerically design orthogonal Discrete Frequency-Coding Waveforms(DFCWs)with good correlationproperties for MIMO radar.Some of the designed results are presented,and their correlation propertiesare better than those presented in literatures.The effect of Doppler frequency shift on the performanceof these signals is simply investigated.Simulation results and comparisons show that the proposedalgorithm is more effective for the design of DFCWs with superior aperiodic correlation properties.

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.

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.

Computationally Efficient MUSIC-Based Algorithm for Joint Direction of Arrival (DOA) and Doppler Frequency Estimation in Monostatic MIMO Radar

The problem of joint direction of arrival (DOA) and Doppler frequency estimation in monostatic multiple-input multiple-output (MIMO) radar is studied and a computationally efficient multiple signal classification (CE-MUSIC) algorithm is proposed.Conventional MUSIC algorithm for joint DOA and Doppler frequency estimation requires a large computational cost due to the two dimensional (2D) spectral peak searching.Aiming at this shortcoming,the proposed CE-MUSIC algorithm firstly uses a reduced-dimension transformation to reduce the subspace dimension and then obtains the estimates of DOA and Doppler frequency with only one-dimensional (1D) search.The proposed CE-MUSIC algorithm has much lower computational complexity and very close estimation performance when compared to conventional 2D-MUSIC algorithm.Furthermore,it outperforms estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm.Meanwhile,the mean squared error (MSE) and Cramer-Rao bound (CRB) of joint DOA and Doppler frequency estimation are derived.Detailed simulation results illustrate the validity and improvement of the proposed algorithm.

Entropy-based multipath detection model for MIMO radar

An optimized detection model based on weighted entropy for multiple input multiple output (MIMO) radar in multipath environment is presented. After defining the multipath distance difference (MDD), the multipath received signal model with four paths is built systematically. Both the variance and correlation coefficient of multipath scattering coefficient with MDD are analyzed, which indicates that the multipath variable can decrease the detection performance by reducing the echo power. By making use of the likelihood ratio test (LRT), a new method based on weighted entropy is introduced to use the positive multipath echo power and suppress the negative echo power, which results in better performance. Simulation results show that, compared with non-multipath environment or other recently developed methods, the proposed method can achieve detection performance improvement with the increase of sensors.

Non-fluctuating target detection in low-grazing angle with MIMO radar

The non-fluctuating target detection in low-grazing angle using multiple-input multiple-output(MIMO) radar systems was studied, where the multipath effects are very abundant. The performance of detection can be improved via utilizing the multipath echoes. First, the reflection coefficient considering the curved earth effect is derived. Then, the general signal model for MIMO radar is introduced for non-fluctuating target in low-grazing angle. Using the generalized likelihood ratio test(GLRT) criterion, the detector of non-fluctuating target with multipath was analyzed. The simulation results demonstrate that the MIMO radar outperforms the conventional radar in non-fluctuating target detection and show that the performance can be enhanced markedly when the multipath effects are considered.

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.

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.

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.

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.

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.

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.