NDLI: Kalman particle filtering algorithm for symmetric alpha-stable distribution signals with application to high frequency time difference of arrival geolocation

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Kalman particle filtering algorithm for symmetric alpha-stable distribution signals with application to high frequency time difference of arrival geolocation

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Kalman particle filtering algorithm for symmetric alpha-stable distribution signals with application to high frequency time difference of arrival geolocation

Content Provider	IET Digital Library
Author	Xia, Nan Wei, Wen Li, Jingchun Zhang, Xiaofei
Abstract	In this study, a non-linear filtering algorithm for state estimation with symmetric alpha-stable (SαS) noise is presented. The dynamic system model investigated here can be described by a linear state-space equation and a non-linear observation equation. The contribution of this study can be summarised as follows. First, particle filtering approach is employed for coarse estimation of the unknown parameters and then Kalman filter is performed to achieve better estimation. Second, SαS noise is considered as the additive disturbance in the observed signal and Gaussian approximation is used to compute the characteristics. Third, the calculation complexity is analysed according to the proposed algorithm. The proposed method is compared with the standard particle filter, extended Kalman filter and unscented Kalman filter for static parameter estimation of a periodic signal. As a practical application, the proposed method is used in high frequency source localisation based on time difference of arrival measurements.
Starting Page	619
Ending Page	625
Page Count	7
ISSN	17519675
Volume Number	10
e-ISSN	17519683
Issue Number	Issue 6, Aug (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/10/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2014.0279
Journal	IET Signal Processing
Publisher Date	2016-08-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Approximation Theory Calculation Complexity Coarse Estimation Complexity Dynamic System Model Filtering Method in Signal Processing Gaussian Approximation Gaussian Processes High Frequency Source Localisation High Frequency Time Difference of Arrival Geolocation Interpolation And Function Approximation Kalman Filter Kalman Particle Filtering Algorithm Linear State-Space Equation Navigation Nonlinear Filter Nonlinear Filtering Algorithm Nonlinear Observation Equation Numerical Analysis Parameter Estimation Particle Filter Particle Filtering Approach Periodic Signal Radio Navigation And Direction Finding State Estimation Static Parameter Estimation Statistics Symmetric Alpha-stable Distribution Signal Symmetric Alpha-stable Noise SαS Noise Time Difference of Arrival Measurement Time-of-arrival Estimation Unscented Kalman Filter
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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