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Target tracking problem has many practical applications in real life. Insubmarines, target tracking is done using, preferably, passive sensors. Thesesensors measure only the bearing angles between the observed target and theownship. Therefore, this problem is generally referred as bearing only targettracking or target motion analysis. The classical approach is to use a stateobserver based filter, i.e. Extended Kalman Filter, to estimate the range,course and speed of the target, using only the bearings. In recent studies, theproblem is solved as a global optimization problem by utilizing evolutionaryalgorithms with respect to some objective functions. In this study, weinvestigate the effect of the commonly used cost functions on the performanceof the TMA algorithms. Particularly, we investigate the cost functions based onbearing differences and equidistant line segments. The simulation results showthat the latter gives a sub-optimal solution to the target motion analysisproblem, compared to the former.

Analysis of performance criteria for optimization based bearing only target tracking algorithms