Title :
MAP joint identification and estimation for over-the-horizon radar
Author :
Feng Xiaoxue ; Liang Yan ; Jiao Lianmeng
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
Abstract :
Target tracking in over-the-horizon radar (OTHR) is a challenging problem due to the existence of multiple propagation modes between the transmitter, target and receiver. Up to present, all OTHR based target-tracking methods require that the ionospheric parameters should be available via the ionosondes. However, the ionosondes can not be arbitrary deployed, for example, in sea area or hostile zone. Besides, the couple of mode identification and state estimation (estimation errors increase identification risk while identification mistake leads to estimation divergence to the actual value) in OTHR target tracking is another challenge. In this paper, a maximum-a-posterior joint mode identification and state estimation algorithm independent of ionosondes is proposed. Firstly, the joint optimization function is derived based on Maximum a Posteriori Penalty Function method. Through modeling both slant returns of different ray models and ray model sequence modeled as Markov process, mode identification can be performed recursively in Viterbi algorithm. Finally, though defining a quadratic penalty function, state estimation can be solved via extended Kalman filter. The simulation shows that the proposed method can effectively estimate the target state and ionospheric heights without the help of ionosondes.
Keywords :
Kalman filters; Markov processes; ionospheric measuring apparatus; maximum likelihood estimation; radar tracking; target tracking; Markov process; OTHR; Viterbi algorithm; estimation errors; extended Kalman filter; ionosondes; ionospheric parameters; joint optimization function; maximum a posteriori penalty function method; maximum-a-posterior joint mode identification; over-the-horizon radar; propagation modes; quadratic penalty function; ray model sequence modeled; state estimation algorithm; target tracking; Joints; Optimization; Radar tracking; State estimation; Target tracking; Ionospheric Parameters; Mode Identification; Over-the-Horizon Radar (OTHR); State Estimation;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese