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For many nonlinear estimation problems, classical lower bounds such as the Cramer-Rao bound (CRB) can characterize the mean squared error (MSE) performance only in the asymptotic region. While more powerful bounds like the Ziv-Zakai bound (ZZB) can also predict the best MSE performance in the nonasymptotic region, they may complicate the computation to an unaffordable extent. In this paper, for estimators...
This paper addresses the problem of adaptive multiple-input multiple-output (MIMO) radar detection in heterogeneous environment with compound-Gaussian clutter. The clutter covariances are assumed to be random and different from one transmit/receive pair to another with a priori knowledge about the environment. A two-step strategy is employed to design adaptive detector. Firstly, we obtain the generalized...
In this paper, two different Cramer-Rao bounds are compared for joint target position and velocity estimation for either active or passive radar. The first bound considers the case where the target has been previously detected in a given range cell, so that propagation loss can be estimated. The second bound does not assume the target can be localized to a given range cell. The comparisons are carried...
In this paper, we focus on the theoretical localization accuracy of two localization algorithms in noncoherent MIMO radar systems with widely separated antennas. The first one is the optimal method for multitarget localization which is simply to expand the dimension of the parameter vector and thus perform a global maximum of the joint likelihood function of all the targets. The second one is a suboptimal...
Bayesian bounds incorporate prior knowledge on parameters of interest. Nonlocal bounds can provide more accurate prediction of the performance of estimators over the full range of possible mean-squared errors. For example, local bounds, such as the Cramer-Rao bound (CRB), provide especially inaccurate predictions under low signal-to-clutter-plus-noise ratio (SCNR) conditions. In this paper, we derive...
This work investigates the target localization capabilities of a multiple input multiple output (MIMO) radar with multiple widely separated transmit and receive sensor arrays. The corresponding Cramer-Rao lower bound (CRLB) is derived for noncoherent estimation of a target's location. The derived CRLB can be seen as a generalization of the CRLB for a monostatic radar with a single sensor array. It...
In this paper, we consider the problem of waveform design for a multiple-input multiple-output over-the-horizon (MIMO-OTH) radar system corrupted by colored Gaussian noise and signal dependent clutter. The discrete prolate spheroidal (DPS) sequences are applied to construct the waveforms as their band-limited property is suitable for addressing the operational frequency limitations of the MIMO-OTH...
In order to reduce the number of transmissions between a set of sensors and a fusion center in signal detection applications, we propose an algorithm based on ordering and halting the transmissions wisely, which can reduce the data transmission, and thus expended energy and data rate, without sacrificing signal detection performance. Here we consider the specific case of noncoherent signal detection,...
Recent research indicates that one can obtain improved MSE performance from employing a coherent processing approach in MIMO radar with properly placed antennas. This paper demonstrates that the magnitude of these gains decreases with an increase in the product of the number of transmit and receive antennas if the antennas for the noncoherent system are also suitably placed, using a placement which...
The diversity gain of a multiple-input multiple-output (MIMO) system adopting the Neyman-Pearson (NP) criterion is derived for a signal-present versus signal-absent scalar hypothesis test statistic and for a vector signal-present versus signal-absent hypothesis testing problem. The results are applied to a MIMO radar system with M transmit and N receive antennas, used to detect a target composed of...
Multiple-input multiple-output (MIMO) radar can achieve improved localization performance by employing a coherent processing approach with proper antenna positioning. Different from the noncoherent counterpart, coherent processing entails the challenge of ensuring phase coherence of the carrier signals from different distributed radar elements. In this paper, we propose a broadcast consensus based...
Practical realization of the coherent processing in widely separated multiple-input multiple-output (MIMO) radar systems requires the development of implementable techniques to ensure a common notion of phase among all the distributed radar elements. In this work, we present two effective approaches to achieve phase synchronization in coherent MIMO radar systems. The first one is the master-slave...
In this paper, moving target tracking performance in multiple input multiple output (MIMO) radar systems with distributed antennas and non-coherent processing is studied. Due to the use of multiple, widely distributed antennas, MIMO radar architectures support both centralized and decentralized tracking techniques. Each receiving radar may contribute to central processing by providing either raw data...
Initially we formulate a very general hypothesis testing problem where we attempt to distinguish between zero-mean Gaussian clutter-plus-noise only and returns which are a linear transformed version of a zero-mean Gaussian random vector plus this clutter-plus-noise. We show that the diversity gain of the optimum processing for this hypothesis testing problem must be less than or equal to the rank...
In this paper, we focus on a performance bound for joint location and velocity estimation in non-coherent MIMO radars with multiple targets, which has not been studied before. Closed-form expressions for the Cramer-Rao bound are provided for a two-target case. We use numerical simulations to validate the Cramer-Rao bounds and use these bounds to study the performance of a non-coherent MIMO radar system...
A discretetized version of a continuous optimization problem is considered for the case where data is obtained from a set of dispersed sensor nodes and the overall metric is a sum of individual metrics computed at each sensor. An example of such a problem is maximum likelihood estimation based on statistically independent sensor observations. By ordering transmissions from the sensor nodes, a method...
Revisiting an earlier examined multiple-input multiple-output (MIMO) radar waveform design problem which optimizes both minimum mean-square error estimation (MMSE) and mutual information (MI), we formulate a new waveform design problem and provide some further results in this paper, which complements the previous study. More specifically, we present an iterative optimization algorithm based on the...
Joint target position and velocity estimation is considered when a MIMO radar system employs either coherent or noncoherent processing and a suitable antenna placement for the processing employed. A theorem is presented for the case of orthogonal signals in temporally and spatially white noise-plus-clutter which shows that the MSE for the estimate of the noncoherent system approaches that of the coherent...
In a widely separated multiple-input multiple-out (MIMO) radar system with non-coherent receivers, the maximum likelihood estimator (MLE) of target location and the corresponding CRLB matrix are derived. Further, two interactive signal processing and tracking algorithms are developed based on the Kalman filter and the particle filter respectively. For a system with a small number of elements and a...
In this paper, tracking performance of MIMO radar systems with distributed antennas and non-coherent processing is studied. The Bayesian Cramer-Rao bound (BCRB) on target location and velocity tracking is derived and the effect of the radars geometric layout and the target location on tracking accuracies is analyzed. The impact of the number of radars on the estimation errors is examined and the contribution...
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