Abstract: A method for target motion analysis for calculating the track between an observer and a target and estimating its uncertainty includes initializing strongly observable state components into strong state vectors and weakly observable state components to form a weak state analysis grid. Initial probability density functions are calculated from all components. The method then iteratively calculates strong state gradients, target track direction, and updates strong state vectors over the analysis grid. Probability density functions are recalculated. Calculations are reiterated if the probability density functions change more than an information threshold. The strong state vectors and weak state probability density functions are provided as output if the information threshold is not exceeded.

Abstract: An underwater target tracking capability is disclosed for a grid-search technique utilizing parameter evaluation plot techniques comprising processing acoustic sonar measurements in conjunction with additional kinematics and environmental information. In the implementation described here, the measurements considered are passive broadband sphere bearings together with limiting knowledge of target speed and range at initial detection. These information sources are processed in a manner especially suited to enable rapid response to the emerging tactical situation.

Abstract: A method for performing mutations in a genetic algorithm-based underwater oustic contact tracking system includes the steps of: (i) providing an initially ordered list of bit numbers; (ii) selecting a random number from a uniform distribution of numbers; (iii) performing an inverse mapping of the selected random number via a binomial distribution, to determine a number of bits to mutate; (iv) determining if mutation is to be performed; (v) selecting particular bits to mutate; (vi) complementing selected bits; and (vii) outputting mutated contact state variables. The invention further contemplates a system for performing the above method.

Abstract: A system for providing an iterative method of assessing accuracy of selected models of physical phenomena and for determining selection of alternate models in response to a data sequence in the presence of noise. Initially, a residual sequence is generated reflecting difference values between in response to said data sequence and an expected data sequence as would be represented by a selected model. Feature estimate values of a plurality of predetermined data features in the residual sequence are then generated. In response to the feature estimate values, a threshold value is generated for each feature at an estimated ratio of data to noise power.