Channel Simulation and Tracking Performance Comparison of LMS, RLS and Kalman Filter
Date Issued
2011
Date
2011
Author(s)
Tzeng, Jiun-Hau
Abstract
We want to compare the performances of LMS, RLS and Kalman filter on the optimum condition. But we may not get the proper characteristics of channel impulse response (CIR) and the information of SNR from real data. Hence, we use simulation data to guarantee that we track channel on the optimum condition. We also expect that the simulation data is similar to the real condition. First, we get the simulator parameters from the real data. Then we use the parameters and channel model method to simulate the received signal. Therefore we can compare the performances of three tracking algorithms, LMS, RLS, Kalman filter on the condition of different fluctuations of CIR. It shows that the performance of Kalman filter is much better than LMS and RLS in sundry fluctuations of CIR. And the performance of RLS is better than LMS on the optimum condition.
Subjects
Tracking Performance
Forgetting Factor
Step Size
Least Mean Square Algorithm
Recursive Least Square Algorithm
Kalman Filter
Underwater Acoustic Channel
Type
thesis
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