Particle Estimation Algorithm Using Anglebetween Observation Vectors for Nonlinear System State

LIANG Jun; PENG Yu; PENG Xiyuan

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Article Navigation > Chinese Journal of Electronics > 2009 > 18(4): 700-702

LIANG Jun, PENG Yu, PENG Xiyuan. Particle Estimation Algorithm Using Anglebetween Observation Vectors for Nonlinear System State[J]. Chinese Journal of Electronics, 2009, 18(4): 700-702.

Citation:

LIANG Jun, PENG Yu, PENG Xiyuan. Particle Estimation Algorithm Using Anglebetween Observation Vectors for Nonlinear System State[J]. Chinese Journal of Electronics, 2009, 18(4): 700-702.

LIANG Jun, PENG Yu, PENG Xiyuan. Particle Estimation Algorithm Using Anglebetween Observation Vectors for Nonlinear System State[J]. Chinese Journal of Electronics, 2009, 18(4): 700-702.

Citation:

LIANG Jun, PENG Yu, PENG Xiyuan. Particle Estimation Algorithm Using Anglebetween Observation Vectors for Nonlinear System State[J]. Chinese Journal of Electronics, 2009, 18(4): 700-702.

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Particle Estimation Algorithm Using Anglebetween Observation Vectors for Nonlinear System State

Received Date: 2008-08-01
Rev Recd Date: 2008-12-01
Publish Date: 2009-11-25

Abstract

Abstract

A particle estimation algorithm where theweight of the particle is related to angle between observation vectors is presented for nonliear system state. Whenthe likelihood has a bimodal nature, this algorithm leads tomore accurate state estimates than Sequential importanceresampling (SIR), Auxiliary particle filter (APF), Regularized particle filter (RPF), and Gaussian particle filter(GPF).
- Nonliear system,
- State estimation,
- Particle filter,
- Sequential importance resampling (SIR),
- Auxiliary particle filter (APF),
- Regularized particle filter(RPF),
- Gaussian particle filter (GPF).