Title :
Real - Time Sequential Kalman Filter Sensor Registration Algorithm
Author :
Da, Li ; Shaohong, Li
Author_Institution :
Sch. of Electron. & Inf. Eng., BeiHang Univ.
Abstract :
A real-time sequential Kalman filter (RTSKF) registration algorithm is presented to correct the dynamic systematic errors based on local tracks. It is accomplished by constructing pseudomeasurements of the sensor biases with additive zero-mean, white noises. Then the sensor bias estimates are obtained dynamically by using sequential process of Kalman filter. Finally, Monte Carlo simulations are employed to evaluate the performance of the proposed algorithm
Keywords :
Kalman filters; Monte Carlo methods; error correction; white noise; Monte Carlo simulation; RTSKF registration algorithm; additive zero-mean noise; dynamic systematic error correction; local tracking; performance evaluation; pseudomeasurements; real-time sequential Kalman filter; sensor bias; white noise; Azimuth; Command and control systems; Iterative algorithms; Least squares methods; Maximum likelihood estimation; Radar tracking; Real time systems; Sensor systems; State estimation; Surveillance; real-time; sensor registration; sequential Kalman filter;
Conference_Titel :
Radar, 2006. CIE '06. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
0-7803-9582-4
Electronic_ISBN :
0-7803-9583-2
DOI :
10.1109/ICR.2006.343450
