多径环境中目标参量的估计

提出了一种多径环境中目标参量估计的新方法，这种方法以时延估计为基础，将目标的方位信息以及速度信息作为状态参量，利用卡尔曼滤波对各个参量进行估计。作者对该方法进行了理论分析，并利用解卷积时延估计技术在ＰＣ机上做了仿真仿真结果表明，这种方法能够准确地估计出多径环境中目标的方位信息和速度信息。

Estimation of Position and Velocity of Moving Objects in Multi-Path Environment

In China's scabed petroleum exploration work, there is a need to be constantly aware ofthe positions and velocities of many moving objects. In this paper we present our research results on how to provide such information under the difficult condition that multi-path effectexists under water.we establish a multi-path model as shown in Fig. 2. Echoes are renected from both seasurfsce and sea bottom. The position coordinates and velocity components are estimated withKalman filter in accordance with dynamic-parameter estimation diagram proposed by Hassab in 1983 [2]. Fig. 3 presents the simulation results for three position coordinates x, y andz and three velocity components vx, v and vz. In Fig. 3, K represents iteration times. Evenfor a not very large K (in Fig. 3, the horizontal axis ends at K=24), the estimated values ofx, y , z, vx, vy and vz either approach its real values or remain quite close to them.Our method appears to be better than High Resolution method in this respect: it provides the position coordinates of real objects only and does not include unreal objects'