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In this paper, the problem of the waveform design for colocated multiple-input multiple-output (MIMO) radars is considered in two parts. In the first part, we design transmit waveform in order to approximate the desired beampattern with low number of samples in the transmitter. Unlike the traditional waveform design methods, in our solution, waveforms are designed for a specific number of samples. Also, the constant envelope constraint that is an important practical constraint is considered. In the second part, we jointly design the transmit waveform and receive filter by a sequential algorithm, considering a priori information of target and interference angle locations. We have evaluated... 

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... 

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 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... 

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... 

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... 

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 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 paper, a sparsity-aware target localization method in multiple-input-multiple-output (MIMO) radars by utilizing time difference of arrival (TDOA) measurements is proposed. This method provides a maximum likelihood (ML) estimator for target position by employing compressive sensing techniques. Also, for fast convergence and mitigating the mismatch problem due to grid discretization, we address a block-based search coupled with an adaptive dictionary learning technique. The Cramer-Rao lower bound for this model is derived as a benchmark. Simulations results are included to verify the localization performance  

This letter presents a novel solution for the problem of moving target localization in multiple-input multiple-output radar systems. The localization problem is formulated, based on least squares criterion, as a non-convex optimization problem and solved by semidefinite relaxation method. Then, an improvement technique, refining the initial solution by estimating the error terms, is proposed. Numerical simulations demonstrate that the proposed method achieves a significant performance improvement over the state-of-the-art methods. Specifically, the proposed method is shown to be more robust to the noise level compared with the existing algorithms. © 1997-2012 IEEE  

In this letter, we consider the problem of waveform design in colocated multiple-input multiple-output radars in order to obtain a desired beampattern. In this problem, practical constraints, such as constant envelope (CE) and low peak-to-average power ratio, are very important. Therefore, we propose a simple method to generate some practical waveforms, such as different versions of phase-shift keying and pulse-amplitude modulation. We map a non-CE to the desired finite alphabet by a mapping function (MP). In the proposed method, first, the values of cross-correlation relationship between the input and the output of MP are calculated in a few points, and then, using radial point... 

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... 

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... 

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... 

The authors deal with the robust design of multiple-input-multiple-output (MIMO) space-time transmit code (STTC) and space-time receive filter (STRF) for a point-like target embedded in signal-dependent interference. Specifically, they assume that the radar exploits knowledge provided by dynamic environmental database, to roughly predict the actual scattering scenario. Then, they devise an iterative method to optimise the (constrained) STTC and the (constrained) STRF which sequentially improves the worst-case (over interfering scatterers statistics) signal-to-interference-plus-noise ratio (SINR). Each iteration of the algorithm is handled via solving two (hidden) convex optimisation... 

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... 

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....