Continuous-discrete maximum correlation entropy target tracking method based on variational Bayesian theory

A variational Bayesian and maximum correlation entropy technology, applied in the field of continuous-discrete maximum correlation entropy target tracking, can solve problems such as inferior and unknown time-varying noise processing, achieve enhanced robustness, solve measurement anomalies, good stability effect

Pending Publication Date: 2022-05-06
AIR FORCE UNIV PLA
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Problems solved by technology

[0005] Considering the above research, although the VB filtering method can effectively estimate the unknown time-varying noise, its ability to suppress the non-Gaussian measurement mutation value is not as good as the MCC filtering; similarly, compared with the VB filtering method, the MCC filtering method cannot be very good. Dealing with Unknown Time-Varying Noise

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  • Continuous-discrete maximum correlation entropy target tracking method based on variational Bayesian theory
  • Continuous-discrete maximum correlation entropy target tracking method based on variational Bayesian theory
  • Continuous-discrete maximum correlation entropy target tracking method based on variational Bayesian theory

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Embodiment Construction

[0117] For the complex measurement environment, in order to effectively suppress the unknown time-varying noise and non-Gaussian mutation noise that appear in the measurement, and improve the accuracy of filtering, the present invention combines the maximum correlation entropy criterion with the variational Bayesian criterion, At the same time, the robustness factor and the square root technology are introduced, and applied to the continuous-discrete time system, a square-root continuous-discrete variational Bayesian maximum correlation entropy volumetric Kalman filter (Square-Root Continuous-DiscreteVariational Bayesian Maximum Correntropy Cubature Kalman Filter, SRCD-VBMCCKF) target tracking method, as follows.

[0118] 1. Square root continuous-discrete target tracking method

[0119] 1.1 Build a continuous-discrete target tracking model

[0120] In continuous-discrete time systems, the continuous state model of the target is represented by stochastic differential equation...

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Abstract

The invention discloses a continuous-discrete maximum correlation entropy target tracking method based on a variational Bayesian theory. The continuous-discrete maximum correlation entropy target tracking method comprises the following steps: establishing a continuous-discrete tracking model; introducing a square root tracking method; a time updating process of the SRCD-VBMCCKF target tracking method is established; establishing a measurement updating process of the SRCD-VBMCCKF target tracking method; and an SRCD-VBMCCKF target tracking method of any motion time is established. According to the method, unknown time-varying noise and non-Gaussian heavy tail mutation noise in measurement can be effectively suppressed, and compared with a traditional filtering method, the method has adaptability and robustness.

Description

technical field [0001] The invention relates to a target tracking method, in particular to a continuous-discrete maximum correlation entropy target tracking method based on variational Bayesian theory. Background technique [0002] Azimuth-only target tracking (Wei Jing, Wen Jun, Li Caicai, etc. Auxiliary variable azimuth-only target tracking algorithm [J]. Journal of Xidian University, 2016, 43(1): 167-172.) By obtaining the angle information of the target , and then complete the state estimation of the target. Because it does not actively transmit signals, bearing-only tracking is widely used in navigation and guidance, especially in the field of passive target tracking. The traditional azimuth-only target tracking method considers that the motion model of the target is discrete, and its corresponding measurement model is also discrete. Such a system is called a discrete-discrete filter system. However, the motion model of the dynamic system of target tracking should be ...

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Application Information

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IPC IPC(8): G06T7/246G06T7/277G06F17/13G06F17/16G06N7/00
CPCG06T7/251G06T7/277G06F17/13G06F17/16G06N7/01
Inventor 胡浩然陈树新吴昊何仁珂
Owner AIR FORCE UNIV PLA
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