研究目的
To propose a new filter based on centered error entropy criterion (CEEC) for multipath estimation in non-Gaussian noise environments, overcoming the limitations of existing methods designed for Gaussian noise.
研究成果
The CEEC filter demonstrates better performance than the MEEC filter for multipath estimation in non-Gaussian noise, as it can fix the main peak of the error PDF at the original point and overcome the drawbacks of MEE being shift-invariant and MCC being local optimization.
研究不足
The CEEC estimator is sensitive to the initial state and initial gain matrix, which are areas for future improvement.
1:Experimental Design and Method Selection:
The study proposes a CEEC filter for multipath estimation, utilizing a stochastic information gradient method for optimal filter gain matrix calculation.
2:Sample Selection and Data Sources:
Simulated C/A signal of GPS in a scenario with a direct signal and a multipath signal.
3:List of Experimental Equipment and Materials:
Not explicitly mentioned.
4:Experimental Procedures and Operational Workflow:
Implementation of the CEEC filter in an iterative way using modified Parzen windowing technique for practical application.
5:Data Analysis Methods:
Performance comparison between CEEC filter and MEEC filter in terms of estimation accuracy.
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