The Observation Systems of Emplacement Reconnaissance and Verifying Radar based on Improved Chaos Genetic Algorithms
Wei Pan, Yu Han, Feng Huang, Lichao Ding · 2020
The problem of managing sensors as one of optimal control of the resulting state estimator covariance matrix. Originally posed in the early days of optimal control, this problem has received little attention, despite the proliferation of active sensing systems and sensor networks and the resulting need to target observations to obtain useful state estimates while minimizing energy expenditure. The problem where the parameters of an observation system, to be selected from given set, are controlled in-the-loop. The necessary condition for optimality and a numerical scheme for finding these solutions. Finally, using a convenient parameterization of the ambiguity function for a certain class of pulsed emplacement reconnaissance and verifying radar systems, we apply this theory to optimal tracking of a target with known dynamics.