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The spatial sparsity of targets in the radar scene is widely used in multiple-input multiple-output (MIMO) radar signal processing, either to improve the detection/estimation performance of the radar or to reduce the cost of the conventional MIMO radars (e.g., by reducing the number of antennas). While sparse target estimation is the main challenge in such an approach, here, we address the design of a compressive-sensing-based MIMO radar, which facilitates such estimations. In particular, we propose an efficient solution for the problem of joint power allocation and antenna placement based on minimizing the number of transmit antennas while constraining the coherence of the sensing matrix.... 

In this paper, we analyze the accuracy of target localization in multiple-input multiple-output (MIMO) radars with widely-separated antennas. The relative target-antennas geometry plays an important role in target localization. We investigate the optimal placement of transmit and receive antennas for coherent and non-coherent processing, based on maximizing the determinant of the Fisher information matrix (FIM), which is equivalent to minimizing the error ellipse area. The square root of the average determinant of the FIM can be expressed as a product of three parameters, namely the equivalent single radar gain, coherency gain and geometry gain. It is shown that the coherency gain of... 

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 paper deals with the moving target localization problem from time delay and Doppler shift measurements in a distributed multiple-input multiple-output radar system. An algebraic closed-form two-stage weighted least squares solution is presented to locate the target position and velocity. In the first stage, a set of pseudo-linear equations is established by introducing and decreasing the nuisance parameters. Then, two quadratic equations are obtained in terms of the nuisance parameters by considering relationships among them and the target position and velocity. By applying the elimination method that gives the nuisance parameters and substituting them into the localization problem, the... 

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... 

In this letter, an efficient estimator for 3-D target localization in distributed multiple-input multiple-output (MIMO) radars using time delay (TD) and angle of arrival (AOA) measurements is proposed. First, an approximately equivalent maximum likelihood (ML) estimation problem is formulated. Then, the aforementioned ML problem is recast into a convex optimization problem for which we derive a semi closed-form solution that eventually boils down to finding the roots of certain polynomials. Using numerical simulations, we demonstrate that the proposed estimator reaches the Cramer-Rao lower bound (CRLB) up to relatively high Gaussian measurement noise levels. Furthermore, the proposed method... 

In this study, an algebraic closed-form method for jointly locating the target and refining the antenna positions in multiple-input-multiple-output radar systems is proposed. First, a set of linear equations is formed by non-linear transformation and nuisance parameters elimination, and then, an estimate of the target position is obtained by employing a weighted least-squares estimator. To jointly refine the target and antenna positions, the associated error terms are estimated in the sequence. The proposed method is shown analytically and confirmed by simulations to attain the Cramér-Rao lower bound performance under small-error conditions. Numerical simulations are given to support the... 

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, a novel solution for the problem of joint moving target and antenna localization in the distributed multiple-input multiple-output (MIMO) radar systems is proposed. The localization problem in the presence of antenna location uncertainty is formulated as a maximum likelihood (ML) estimation problem, which is then recast into convex form by defining some auxiliary variables and applying semidefinite relation (SDR) technique. Next, an algebraic closed-form estimator is proposed to jointly estimate the target and the antennas error terms and refine their uncertain values. The proposed method is shown analytically and verified by the numerical simulations to be an efficient... 

In this study, the authors propose an algorithm to reduce the effect of antenna location uncertainty for locating moving targets in multiple-input multiple-output (MIMO) radar systems. The proposed method is a closed-form solution which employs the measurements of multiple independent targets to alleviate the antenna location uncertainties. The authors establish a pseudo-linear set of equations by using the range and the range-rate auxiliary parameters, which allows the problem to be solved using a two-stage weighted least squares estimator. The proposed method is shown analytically and confirmed by simulations to attain the Cramer-Rao lower bound under small error conditions. The... 

This paper concentrates on the target localization problem in a distributed multiple-input multiple-output radar system using the bistatic range (BR) measurements. By linearizing the BR measurements and considering the relationship between the nuisance parameter and the target position, a constrained weighted least squares (CWLS) problem is formulated, which is an indefinite quadratically constrained quadratic programming problem. Since the constraint is non-convex, it is a nontrivial task to find the global solution. For this purpose, an improved Newton's method is applied to the CWLS problem to estimate the target position. Numerical simulations are included to examine the algorithm's... 

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  

In this paper, the problem of locating a target in a distributed multiple-input multiple-output radar system using bistatic range measurements is addressed. An algebraic closed-form two-stage weighted least squares solution for the considered problem is developed and analyzed. In the first stage, we establish a set of linear equations by eliminating the nuisance parameters first and then we apply a weighted least squares estimator to determine the target position estimate. In the second stage, in order to improve the localization performance and refine the solution of the first stage, an estimate of the target position estimation error is obtained. The final solution is obtained by... 

Multiple-input multiple-output (MIMO) radars have attracted much attention for their superior ability to enhance a system's performance. In this study, the authors' goal was the study of the spatial multiplexing gain of MIMO radars with widely separated antennas (WS-MIMO), which the authors showed that is equal to the number of unambiguously detectable targets. They obtained this number from two different aspects: first, by defining the ambiguity function of a WS-MIMO radar in the case of multiple targets, suitable for such purpose; Second, by modelling the MIMO radar system with a MIMO wireless channel. They showed that a MIMO radar is indeed a MIMO wireless system communicating the... 

It is shown that the detection performance can be significantly improved using the recent technology of multiple-input multiple-output (MIMO) radar systems. This is a result of the spatial diversity in such systems due to the viewing of the target from different angles. On the other hand, the moving target indication (MTI) processing has long been known and applied in the traditional pulse radars to detect weak moving targets in the presence of strong clutter signals. The authors propose a procedure based on the compressive sensing idea, in order to apply the MTI processing in a MIMO radar with widely separated antennas. Although a clutter is included in the signal model and a different... 

Multiple input multiple output (MIMO) radar is known for its superiority over conventional radar due to its antenna and waveform diversity. However, the increased hardware cost (due to multiple transmitters and receivers), power consumption (due to multiple transmitters and pulses), and computational complexity (due to numerous pulses) form the drawbacks of MIMO radar. On one hand, a higher estimation accuracy is required, but on the other hand, a lower number of active antennas/pulses is desirable. Therefore, in this paper, by proposing a convex optimization approach for the general case of transmitter-receiver-pulse selection, we will minimize the total number of active antennas/pulses in... 

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... 

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...