Abstract
A new filter which could satisfy most of the requirements of a modern-day tracking estimator was developed in this chapter. This estimator is designed particularly for the purpose of the undersea tracking purpose, where the erroneous bearing information is the only data available. The technique involved is to combine the various important techniques available in the literature to develop a less complex more robust estimator. First of all, the weighted expectation of the current and the previously received sensor measurements are computed. These named as the preprocessed measurements contain less variance of noise are in turn applied to the various nonlinear algorithms such as UKF. The consolidation of all the UKF outputs is done in such a way that the least mean square error is obtained. This is possible with the least squares estimation filter (WLSE). The output of WLSE is a much superior one because of performing the refining procedure in two different steps. Monte Carlo simulations are performed to verify the robustness of the introduced mechanism. The algorithm is tested for tracking a submarine located in various quadrants, various ranges, and various noise levels.
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Ravi Kumar, D.V.A.N., Koteswara Rao, S., Padma Raju, K. (2018). Design of a Robust Estimator for Submarine Tracking in Complex Environments. In: Anguera, J., Satapathy, S., Bhateja, V., Sunitha, K. (eds) Microelectronics, Electromagnetics and Telecommunications. Lecture Notes in Electrical Engineering, vol 471. Springer, Singapore. https://doi.org/10.1007/978-981-10-7329-8_28
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