Target tracking and guidance using particles

Salmond, David; Everett, Nick; Gordont, N.J.

doi:10.1109/acc.2001.945668

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…5a and Fig. 5b record the chasing procedure with complex non-Gaussian double-mode noise stated in (18)(19)(20)(21). Similarly, Fig.…”

Section: Simulationsmentioning

confidence: 95%

“…However, in many recent applications the fact that the Gaussian assumption does not hold accurately forces people to study filters which do not require the Gaussian assumption. The Particle Filter (PF) [20], which is based on Bayesian reasoning, is one of such filters, popularly used in non-Gaussian non-linear tracking applications.…”

Section: State Estimation Using Particle Filtermentioning

confidence: 99%

“…2) Results should not change, which means if theoretically an evader can be caught when pursuers following optimal strategies, the sub-optimality strategies should also be able to ensure pursuers to catch it. Based on [23], a sub-optimal decentralized multi-pursuer multi-evader approach which can deal with multi-mode non-Gaussian noise with particle filtering [20] is studied. This approach can handle different objective priorities (to capture more or to capture higher value) and can deal with multiple superior evaders simultaneously in noisy environments.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Decentralized Approach to Pursuer-Evader Games with Multiple Superior Evaders in Noisy Environments

Wei

Chen

Cruz

et al. 2007

2007 IEEE Aerospace Conference

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Abstract-Few pursuer-evader (PE) game algorithms allow for real-time applications for (1) multi-pursuer-multi-evader situations, (2) noisy environments, and (3) evaders with superior control resources such as higher speeds. This paper introduces a real-time decentralized approach for such games. A sufficient condition for capturing a superior evader is proposed. A particle filter is applied to the complex non-Gaussian multi-model noise. Simulations confirm the efficiency of this approach.

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“…5a and Fig. 5b record the chasing procedure with complex non-Gaussian double-mode noise stated in (18)(19)(20)(21). Similarly, Fig.…”

Section: Simulationsmentioning

confidence: 95%

Section: State Estimation Using Particle Filtermentioning

confidence: 99%