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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...
Exploiting the received signals, which are usually not employed in the traditional OTH radar for ionospheric parameter estimation, we study joint estimation of target and ionospheric parameters for multiple-input multiple-output skywave OTH (MIMO-OTH) radar. We employ a parabolic layer model to characterize the ionospheric distortions. We model the target and ionospheric parameters as deterministic...
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,...
A discretized 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...
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...
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