基于MGEKF的单站无源定位跟踪算法

Single-observer Passive Location and Tracking Algorithms based on Modified Gain Extended Kalman Filter

单站无源定位跟踪技术具有隐蔽性强、设备简单、系统相对独立等优点,有着广阔的应用前景。为了提高定位精度和收敛速度以满足实时化需求,在现有的基于多普勒变化率的单站无源定位算法的基础上,详细推导了基于MGEKF的定位算法以解决EKF算法的不稳定性,并通过计算机仿真比较了两种算法的性能,结果表明MGEKF定位算法提高了定位精度、收敛速度和稳定度,定位结果能够满足实际需求。

Single-observer passive location and tracking technology has many merits, such as simple equipment and independent system, and can be widely used in the engineering field. To improve the location precision and convergence speed and meet the real-time requirements, an algorithm based on the existing algorithm of Doppler changing rate is developed. A modified gain extended Kalman filter is introduced to solve the instability of extend Kalman filter. The performances of these algorithms are compared by computer simulations. The results show that the MGEKF location algorithm which enhances the location precision, convergence speed and stability, can satisfy the demands of real-time systems.