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We focus on the design of a Kalman filter-based algorithm to track multiple targets in range and azimuth. The detection stage implements a multitarget strategy aimed at collecting and eventually processing all target measurements. Existing tracks are updated using a joint probabilistic data association (JPDA) algorithm to handle the data association problem.We model target echoes as coherent pulse trains in white Gaussian noise with unknown power. The performance analysis assumes a maritime scenario and shows that the proposed tracker outperforms more conventional approaches. [ABSTRACT FROM AUTHOR]

Blind source separation (BSS) and blind beamforming schemes attempt to separte additive source signals, collected at a sensor array, and their direction-of-arrival (DOA). To this extent, many different and powerful algorithms have been produced to accomplish these tasks. However, unlike an optimal or adaptive method, an algebraic method for BSS and blind beamforming has the relative advantage of simplicity. This paper investigates such technique that provides closed-form, algebraic expression for BSS and beamforming in terms of performance and reliability. We provide these results, as well as a summary of the properties, and possible uses for this technique, in contrast to more optimal, adaptive techniques. [ABSTRACT FROM AUTHOR]