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We propose a novel non-parametric technique for source localization with passive sensor arrays. Our approach involves formulation of the problem in a variational framework where regularizing sparsity constraints are incorporated to achieve superresolution and noise suppression. Compared to various source localization schemes, our approach offers increased resolution, significantly reduced sidelobes, and improved robustness to limitations in data quality and quantity. We demonstrate the effectiveness of the method on simulated data.

Abstrucf -In this paper we carry out a detailed analysis of the multiple time scale behavior of singularly perturbed linear systems of the formwhere A ( < ) is analytic in the small parameter e. Our basic result is a uniform asymptotic approximation to exp A ( e ) r that we obtain under a certain multiple semistability condition.This asymptotic approximation gives a complete multiple time scale decomposition of the above system and specifies a set of reduced order models valid at each time scale.Our contribution is threefold. 1) We do not require that the state variables be chosen so as to display the time scale structure of the system.2) Our formulation can handle systems with multiple ( > 2) time scales and we obtain uniform asymptotic expansions for their behavior on [0,00]. 3) We give an aggregation method to produce increasingly simplified models valid at progressively slower time scales.

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There exist a number of mathematical procedures for designing discrete-time compensators. However, the digital implementation of these designs, with a microprocessor for example, has not received nearly as thorough an investigation. The finite-precision nature of the digital hardware makes it necessary to choose a computational structure that will perform adequately with regard to the initial objectives of the design. This paper describes a procedure for estimating the required fixed-point coefficient wordlength for any given computational structure for the implementation of a singleinput single output LQG design. The results are compared to the actual number of bits necessary to achieve a specified performance index.* This work was performed in part at the MIT Laboratory for Information and Decision Systems with support provided by NASA Ames under grant NGL-22-009-124 and in part at the Charles Stark Draper Laboratory.