Neural network aided Kalman filtering for multitarget tracking applications
| Autor: | V. Vaidehi, M. Chokkalingam, N. Chitra, C. N. Krishnan |
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| Rok vydání: | 2001 |
| Předmět: |
Scheme (programming language)
Moving horizon estimation Engineering Radar tracker General Computer Science Artificial neural network Estimation theory Computer science business.industry Tracking system Filter (signal processing) Kalman filter Tracking (particle physics) Backpropagation Adaptive filter Extended Kalman filter Control and Systems Engineering Fast Kalman filter Computer vision Artificial intelligence Electrical and Electronic Engineering business computer computer.programming_language |
| Zdroj: | Computers & Electrical Engineering. 27:217-228 |
| ISSN: | 0045-7906 |
| DOI: | 10.1016/s0045-7906(00)00013-6 |
| Popis: | The adaptive capability of the Kalman filtering is known to increase by incorporating a neural network into the normal Kalman filter. Current work extends this fact and proposes the neural network aided Kalman filtering scheme for tracking multitargets that are highly manoeuvring. The improvement in the tracking accuracy due to the proposed scheme is presented for various tracking scenarios. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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