中文摘要：

高度估计对于高频地波雷获取三维信息、提高预警能力很有意义。然而目标RCS的随机起伏对高度估计产生严重影响，通过对RCS随机起伏的AR模型建模和模型参数的自适应估计，提出了在RCS变化的条件下高度估计的扩展卡尔曼滤波算法。通过Monte Carlo仿真和外场试验数据的处理，验证了该方法对抑制RCS随机起伏、提高高度估计精度的有效性。

英文摘要：

Estimation of target altitude is quite significant to achieving 3D information and increasing early-warning ability for HF surface wave radar （HHFSWR）. However, random fluctuation of RCS has a serious impact on the estimation of target altitude. By adopting AR model to model the random fluctuation of RCS and self adapting estimating of model parameters, an extended Kalman filter （EKF） algorithm for altitude estimation with varying RCS is proposed in this paper. By Monte Carlo simulating and real data processing, this algorithm＇s validity of repressing the random fluctuation of RCS and improving altitude estimation precision is certified.