1. An Improved Algorithm for High Maneuvering Target Based on Jerk Model.
- Author
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Liu Wang-sheng, Li Ya-an, and Cui Lin
- Subjects
- *
SOUND , *ADAPTIVE filters , *ALGORITHMS , *NOISE , *SAMPLING errors , *RAYLEIGH model , *SIGNAL-to-noise ratio - Abstract
Abstract: Aimed at the inherent flaws of stable deterministic error in conventional algorithm using Jerk model, a modified algorithm was proposed. Jerk model and current Jerk model were fused in the improved algorithm. Weak Jerk maneuver was described by using Jerk model and its system noise variance was adjusted by using the relations of position estimation error and acceleration change rate variance. The strong Jerk maneuver was described by using the current Jerk model, and the statistical characteristics of acceleration change rate variance was depicted by using modified Rayleigh distribution. The tracking accuracy for weak Jerk maneuver was improved, and the tracking ability for strong Jerk maneuver was enhanced by introducing fuzzy distribution function and strong track filter. The theoretical analysis and simulation results show that the defect of conventional Jerk model algorithm is overcome by using the improved algorithm, Jerk sudden maneuver with various intensity can be approached adaptively. Under different intensity signal-to-noise ratios and gauging noises, its error is relatively stable and it has better tracking accuracy. [ABSTRACT FROM AUTHOR]
- Published
- 2012