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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 a multiple aperture technology characterized by the ability to transmit diverse signals at each aperture. This is in contrast to traditional phased array radar whereby a single signals is transmitted with a phase shift applied at each element to enable steering of the transmit beampattern. The hybrid MIMO phased array radar (HMPAR) concept is an outgrowth of the monostatic MIMO construct, in which all sensors have the same view of the far field target which is known as colocated antenna. In the HMPAR, the full transmit array is partitioned into sub-arrays which can be electronically steered in different directions and driven by separate transmit... 

A multiple input multiple output (MIMO) radar is an emerging field which has attracted many researchers recently. In this type of radar, unlike an standard phased array radar, one can choose transmitted probing signals freely 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. These signals can be correlated to each other or noncorrelated. Many papers have investigated beampattern design and waveforming in MIMO radars. One of the most famous approaches for beampattern design is named covariance based... 

Passive localization using MIMO techniques has attracted much attention recently. In such schemes, using multiple antennas at transmitter and receiver sides provides spatial diversity without need for identifiable transmitters. On the other hand, one of the problems facing such approach arises when transmitters of a single frequency network (SFN) are used as non-cooperative transmitters and resolving the signals of multiple transmitters reflected from multiple targets is not trivial at receiver side. Therefore, in order to obtain the diversity gain of MIMO localization schemes, it is necessary to develop a technique to assign each echo arriving at the receiver to a given transmitter. In this... 

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  

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... 

By employing the MIMO (multiple-input-multiple-output) technology in radar, some new problems emerged, that, in order to benefit the MIMO gains in radar, it was necessary to solve them suitably. One of such obstacles is determining the positions of receive antennas in a MIMO radar system with widely separated antennas (WS MIMO radar), since it is shown that the antennas' positions affect the whole system's performance considerably. In this study, a proper receivers' positioning procedure is proposed. To do this end, four criteria are developed based on the proposed MIMO detector and the MIMO ambiguity function. The simulations verify that the proposed positioning procedure improves the... 

Two gains play key roles in recently developed MIMO wireless communication systems: "spatial diversity" gain and "spatial multiplexing" gain. The diversity gain refers to the capability to decrease the error rate of the MIMO channel, while the multiplexing gain implicitly refers to the amount of increase in the capacity of the MIMO channel. It has been shown that there is a fundamental tradeoff between these two types of gains, meaning interplay between increasing reliability (via an increase in the diversity gain) and increasing data rate (via an increase in the multiplexing gain). On the other hand, recently, MIMO radars have attracted much attention for their superior ability to enhance... 

In this paper, a Block Iterative Method with Adaptive Thresholding for Sparse Recovery (BIMATSR) is proposed to recover the received signal in an under-sampled distributed MIMO radar. The BIMATSR scheme induces block sparsity with the aid of a signal-dependent thresholding operator which increases the accuracy of the target parameter estimation task. We have proved that under some sufficient conditions, the suggested scheme converges to a stable solution. Moreover, different simulation scenarios confirm that the BIMATSR algorithm outperforms its counterparts in terms of the target parameter estimation. This superiority is achieved at the expense of slightly more computational complexity. It... 

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... 

In this paper, a Block Iterative Method with Adaptive Thresholding for Sparse Recovery (BIMATSR) is proposed to recover the received signal in an under-sampled distributed multiple-input multiple-output radar. The BIMATSR scheme induces block sparsity with the aid of a signal-dependent thresholding operator which increases the accuracy of the target parameter estimation task. We have proved that under some sufficient conditions, the suggested scheme converges to a stable solution. Moreover, different simulation scenarios confirm that the BIMATSR algorithm outperforms its counterparts in terms of the target parameter estimation. This superiority is achieved at the expense of slightly more... 

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... 

It is a well known fact that using multiple antennas at transmit and receive sides improves the detection performance. However, in such multiple-input multiple-output (MIMO) configuration, proper positioning of transmitters and receivers is a big challenge that can have significant influence on the performance of the overall system. In addition, determining the power of each transmitter under a total power constraint is a problem that should be solved in order to enhance the performance and coverage of such a system. In this paper, we design the Neyman-Pearson detector under the Rayleigh scatter model and use it to introduce a criterion for the antenna placement at both transmit and receive... 

In this letter, an efficient method for solving the multi-target localization problem in distributed MIMO radars is proposed. The proposed method attempts to simultaneously carry out the localization and data association tasks by formulating a mixed-integer optimization problem, which is approximated as a convex problem that can be efficiently solved with a polynomial complexity. Numerical simulations substantiate the efficacy of the proposed method. © 1997-2012 IEEE  

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  

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...