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In this letter, we propose a new accurate approach for target localization in multiple-input multiple-output (MIMO) radars, which exploits the sparse spatial distribution of targets to reduce the sampling rate. We express the received signal of a MIMO radar in terms of the deviations of target parameters from the grid points in the form of a block sparse signal using the expansion around all the neighbor points. Applying a block sparse recovery method, we can estimate both the grid-point locations of targets and these deviations. The proposed approach can yield more accurate localization with higher detection probability compared with its counterparts. Moreover, the proposed approach can... 

This paper studies the placement of antennas in presence of mountains for widely separated multiple-input multiple-output (MIMO) radar. One of the challenges in this configuration is proper placement of the receive antennas in order to achieve good performance. We derived Neyman-Pearson decision rule for target detection. Via several scenarios we show that proper placement of receivers can provide better performance  

Multiple-input multiple-output (MIMO) radars offer higher resolution, better target detection, and more accurate target parameter estimation. Due to the sparsity of the targets in space-velocity domain, we can exploit Compressive Sensing (CS) to improve the performance of MIMO radars when the sampling rate is much less than the Nyquist rate. In distributed MIMO radars, block CS methods can be used instead of classical CS ones for more performance improvement, because the received signal in this group of MIMO radars is a block sparse signal in a basis. In this paper, two new methods are proposed to improve the performance of the block CS-based distributed MIMO radars. The first one is a new... 

This letter investigates the problem of threedimensional (3-D) target localization in multiple-input multipleoutput (MIMO) radars with distributed antennas, using hybrid timedelay (TD) and angle of arrival (AOA) measurements. We propose a closed-form positioning method based on weighted least squares (WLS) estimation. The proposed estimator is shown theoretically to achieve the Cramer-Rao lower bound (CRLB) under mild noise conditions. Numerical simulations also verify the theoretical developments. IEEE  

An algebraic closed-form solution for locating a moving target using a distributed multiple-input multiple-output radar system is proposed. The position and velocity of the target are estimated by presenting a two-stage weighted least squares algorithm. In contrast to existing research, the proposed estimator is shown analytically to be approximately unbiased and its variance is equal to the Cramer-Rao lower bound. Numerical simulations corroborate the theoretical studies and demonstrate the superiority of this algorithm over the existing methods. © 1997-2012 IEEE  

Elliptic localization is an active range-based positioning technique that employs multiple transmitter-receiver pairs, each of which is able to provide separate bistatic range (BR) measurement. In this letter, an algebraic closed-form method for locating a single target from BR measurements using a distributed multiple-input multiple-output (MIMO) radar system is proposed. First, a set of linear equations is established by eliminating the nuisance parameters, and then, a weighted least squares estimator is employed to obtain the target position estimate. To refine the localization performance, the error in the initial solution is estimated in the sequence. The proposed method is shown... 

In this letter, the problem of target localization from bistatic range (BR) measurements in distributed multiple-input multiple-output radar systems is investigated. By introducing nuisance parameters, a pseudolinear set of BR equations is established. Then, a closed-form localization algorithm is developed, based on this pseudolinear set of equations and multistage weighted least squares estimation. This solution is shown analytically to attain the Cramer-Rao lower bound under the small Gaussian noise assumption. Simulations are included to support the theoretical studies. Unlike the existing studies where the variance of BR measurements is assumed to be independent of the corresponding... 

Elliptic localization is a range-based positioning technique exploiting multiple transmitter-receiver pairs, each of which provides separate bistatic range (BR) measurements. In this paper, a novel computationally efficient solution for locating a single target from BR measurements in distributed MIMO radar systems is proposed. Due to nonconvex nature of the associated maximum likelihood (ML) estimation problem, its globally optimal solution is difficult to obtain. We first reformulate the ML estimation as a nonconvex constrained weighted least squares problem. Owing to special structure of the resulting problem, it is recast as a convex problem, whose exact solution can be obtained in... 

In this paper, an algebraic solution for elliptic localization in multiple-input multiple-output (MIMO) radar systems is proposed by taking the uncertainties in antenna positions and their clock parameters into account. Through nonlinear transformation and multi-stage processing, the target position is estimated in closed-form by successively utilizing the weighted least squares estimator. Theoretical analysis demonstrates that the proposed method is able to attain the Cramer-Rao lower bound (CRLB) performance under mild Gaussian error. The conditions for achieving the CRLB are derived as well. The numerical simulations confirm the analytical results and demonstrate significant performance... 

In this paper, we focus on the moving target localization problem in a multiple-input multiple-output radar with widely separated antennas. By exploiting jointly different types of information including time delay, Doppler shift and azimuth and elevation angles of arrival, we develop an algebraic closed-form two-stage weighted least squares solution for the problem. The proposed algorithm is shown analytically to attain the CramerRao lower bound accuracy under the small Gaussian noise assumption. Numerical simulations are included to examine the algorithm's performance and corroborate the theoretical developments  

Compressive sensing (CS) has been widely used in multiple-input-multiple-output (MIMO) radar in recent years. Unlike traditional MIMO radar, detection/estimation of targets in a CS-based MIMO radar is accomplished via sparse recovery. In this article, for a CS-based colocated MIMO radar with linear arrays, we attempt to improve the target detection performance by reducing the coherence of the associated sensing matrix. Our tool in reducing the coherence is the placement of the antennas across the array aperture. In particular, we choose antenna positions within a given grid. Initially, we formalize the position selection problem as finding binary weights for each of the locations. This... 

This letter deals with the problem of moving target localization in distributed multiple-input multiple-output (MIMO) radar systems using time delay (TD) and Doppler shift (DS) measurements. The proposed solution to this problem consists of two stages. In the first stage, an initial estimation of target location is obtained by solving the formulated maximum likelihood (ML) problem based on the TD measurements. In the second stage, by recognizing the obtained position estimate in the previous stage as a priori data and exploiting the DS measurements, another ML problem is formulated, which is efficiently solved via a tractable numerical method to produce a simultaneous estimation of target... 

This letter addresses the problem of joint localization and clock synchronization in distributed multiple-input multiple-output (MIMO) radar systems. While the well-known two-stage weighted least squares (WLS) method provides an acceptable estimate of target position when a rough approximation of antennas clock parameters, the drifts and offsets, is available, its performance can degrade quickly if the level of uncertainty in these values increases. The proposed method offers a solution for synchronizing the clocks while simultaneously improving the target position estimate. The uncertainty in positions of antennas is also taken into account. The presented method is shown to be approximately... 

This article proposes a compressed-domain signal processing (CSP) multiple-input multiple-output (MIMO) radar, a MIMO radar approach that achieves substantial sample complexity reduction by exploiting the idea of CSP. CSP MIMO radar involves two levels of data compression followed by target detection at the compressed domain. First, compressive sensing is applied at the receive antennas, followed by a Capon beamformer, which is designed to suppress clutter. Exploiting the sparse nature of the beamformer output, a second compression is applied to the filtered data. Target detection is subsequently conducted by formulating and solving a hypothesis testing problem at each grid point of the... 

A multiple input multiple output (MIMO) radar system, unlike a conventional phased array radar, can choose freely the signals which transmitted via its antennas to maximize the power around the locations of the specific targets, or more generally to approximate a given transmit beampattern, and also to minimize the cross-correlation of the signals reflected back to the radar by the targets of interest. In this paper we use of phase-coded signals and show how the above desirable features of MIMO radars with some operational consideration can help us to have a desire beampattern. We suppose that for a collection of phase-coded signals, the elements of transmitted signals cross-correlation... 

In a Multiple Input Multiple Output (MIMO) radar unlike conventional phased array radar, we can choose freely between the probing signals transmitted via its antennas to maximize the transmitted power around specific target locations or to approximate a desire beam-pattern in different manners that many papers have taken into consideration so far. In an operational radar or communication environment, one of the usual phenomenon that happens is multipath. In this paper we'd like to take this effect into consideration and show that how this effect can influence our beam-pattern in a covariance based MIMO radar beam-forming. We will show that multipath can change beam-pattern peak direction,... 

A multiple input multiple output (MIMO) radar system is an emerging research field which has attracted many studies in recent years. This type of radar, unlike conventional phased array radar, can transmit different probing signals via its antennas, that may be correlated or uncorrelated with each other. This waveform diversity offered by MIMO radar systems enable superior capabilities compared to conventional phased array radar. Many papers have introduced different ways for beamforming of MIMO radar. In this paper it is desirable to analysis some methods for beamforming of MIMO radars with planar arrays constellation and examine their 3D result beam-pattern of such constellations for... 

A multiple-input multiple-output (MIMO) radar system., unlike a standard phased array radar., can choose freely the probing signals transmitted via its antennas to maximize the power around the locations of the targets of interest., or more generally to approximate a given transmit beam-pattern., or to minimize the cross-correlation of the signals reflected back to the radar by the targets of interest. In this paper it will be shown that how these more degrees of freedom to choose freely between probing signals in a MIMO radar can help to have an omnidirectional beam-pattern for a side-lobe blanker system., and it will be shown that with utilizing MIMO radars for a side-lobe blanker system.,... 

A novel information theoretic code design approach for cognitive multiple-input multiple-output (MIMO) radars is proposed in the current paper. In the suggested solution, we consider an agile multi-antenna radar with spectral cognition and design optimized transmission codes considering practical limitations such as peak-to-average power ratio (PAR) and spectral coexistence in a spectrally crowded environment. As exact performance expressions for the detector is not analytically tractable in this case, an information theoretic approach is taken into account to design the transmission codes. Simulation results illustrate the efficiency of the proposed method  

One of the important obstacles in MIMO (Multiple Input Multiple Output) radars is the issue of designing proper transmit signals. Indeed, the capability of signal design is a significant advantage in MIMO radars, through which, the system can achieve much better performance. Many different aspects of this performance improvement have been considered yet, and the transmit signals have been designed to attain such goal, e.g., getting higher SNR or better detector's performance at the receiver. However, an important tool for evaluating the radar's performance is its ambiguity function. In this paper, we consider the problem of transmit signal design, in order to optimize the ambiguity function...