Improved Based on "Self-Adaptive Turning Rate" Model Algorithm

Abstract

For tracking the object with tracking nonlinear, high maneuvering target，traditional interactive multiple model self-adaptive filter algorithm was usually adopted．The turning rate estimate was very important. However，the performance of turning rate algorithm was not so satisfactory in the  model．Thus，a new the average value turning rate algorithm based on self-adaptive turning model was proposed．Aiming at additional device for turning rate estimation turning model, the parameters α and β were introduced to adjust the roughness of turning rate．Aiming at target constant turning movement and orthogonal turning rate unequal, estimates, turning rate was used the average value model to reduce the noise and error influence. Simulation results showed that the proposed algorithm was more suitable for the objects with Nonlinear, high maneuvering target tracking and could remarkably reduce the sample，and thus achieve much better tracking performance.

DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2602