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摘要:
由于进动锥体目标参数存在耦合，单部雷达不易获取同时参数估计误差较大。针对这一问题，提出了一种联合多部雷达不同视角微动信息进行参数提取与融合的新方法。首先，对进动目标进行了建模和散射点距离像分析，并利用Hough变换实现了锥顶散射点的关联。然后，联立2部雷达的微动信息作为求解单元来对耦合参数进行解耦，求出相应的参数。同时以进动角为例进行了误差方差分析，以融合后误差方差最小为原则对权系数进行了求解，并对其余参数进行了相同的处理。最后，在一个进动周期内，根据求出的锥体顶点坐标和锥旋轴矢量实现了锥体目标空间位置的重构。仿真结果表明该融合方法能够提高参数精度并能对锥体空间位置进行重构。
Abstract:Aimed at the problem that signal radar extracts parameters difficultly and has higher error in estimating parameters due to coupling of precession cone target parameters, a novel algorithm based on uniting the multi-aspect micro-motion information is proposed for parameter extraction and fusion. First, cone-shaped precession model are established and scattering points profile sequence are analyzed. After that, different-aspect conic node scattering point is matched and identified using Hough transform. Then, the micro-motion information of two radars is united as one solving unit to solve the coupling parameters, and other parameters also can be solved. Moreover, precession angle is taken as an example to analyze the variance of error, and each unit is fused by the weighed fusion array based on minimum variance. And other parameters are optimized in the same way. Finally, in one precession period, cone target space position can be reconstructed based on solving the coordinates of conic node and coning vector. Simulation results prove that the proposed method can realize the extraction of high accuracy parameters and cone's reconstruction availably.
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Key words:
- precession /
- Hough transform /
- fusion /
- space position reconstruction /
- performance analysis
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图 3 求解单元1中2部雷达测得的时间-距离像
Figure 3. Time-range profiles measured by two radars of solving unit 1
图 4 提取雷达2散射点A中值和幅值过程
Figure 4. Extraction process of scattering point A's mean value and amplitude value from radar 2
表 1 求解单元估计结果
Table 1. Estimation results of solving unit
参数 理论值 单元1 单元2 单元3 3个单元参数融合 估计值 误差/% 估计值 误差/% 估计值 误差/% 参数融合 误差/% θ 10° 10.332° 3.32 10.317° 3.17 9.774° 2.26 10.184° 1.84 xA -0.275 -0.282 2.54 -0.268 2.54 -0.271 1.45 0.272 1.10 yA 1.286 1.318 2.49 1.307 1.63 1.305 1.48 1.310 1.87 zA 1.262 1.292 2.38 1.288 2.06 1.284 1.74 1.286 1.90 ex 0 0.000 1 0.01 0.000 1 0.01 0.000 1 0.01 0.000 1 0.01 ey 0.707 0.724 2.40 0.720 2.16 0.721 1.98 0.722 2.18 ez 0.707 0.723 2.26 0.720 1.84 0.719 1.70 0.721 1.98 
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表 2 参数估计结果
Table 2. Estimation results of parameters
参数 理论值 雷达1 雷达2 雷达3 3部雷达参数融合 估计值 误差/% 估计值 误差/% 估计值 误差/% 参数融合 误差/% h1 2 m 2.053 m 2.65 1.968 m 1.60 1.972 m 1.40 1.977 m 1.25 h2 0.5 m 0.514 m 2.80 0.512 m 2.40 0.507 m 1.40 0.511 m 1.80 r 0.5 m 0.492 m 1.60 0.507 m 1.40 0.507 m 1.40 0.506 m 1.20 α1 145° 146.58° 1.09 α2 167° 165.74° 0.75 α2 177° 176.15° 0.48
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