基于压缩感知的外辐射源雷达分数阶杂波估计

杨鹏程; 吕晓德; 柴致海; 张丹; 岳琦; 杨璟茂

doi:10.11999/JEIT170079

基于压缩感知的外辐射源雷达分数阶杂波估计

doi: 10.11999/JEIT170079

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出版历程
- 收稿日期: 2017-01-22
- 修回日期: 2017-04-14
- 刊出日期: 2017-11-19

Fractional-delay Clutter Estimation for Passive Radar Based on Compressive Sensing

摘要

摘要: 参考信号信杂比(SCR)是评估外辐射源雷达积累增益损失的重要参数。利用数字电视地面广播(DTTB)辐射源中的PN序列进行信杂比估计时，将出现接收信号相对于本地帧头的分数阶时延问题，导致信杂比估计出现严重偏差。针对该问题，该文利用信号在时延维的稀疏性，提出基于压缩感知的信杂比估计算法。仿真结果表明，该算法对不同强弱的信号都能得到精确的时延和强度估计，从而保证了信杂比估计的准确性。实测数据处理结果表明，实测数据的参考信号信杂比较高，积累损失较小，约为0.5 dB；信杂比与基线距离有关，基线越长信杂比越低，积累损失越大。
- 外辐射源雷达 /
- 压缩感知 /
- 参考信号 /
- 信杂比 /
- 分数阶时延 /
- PN序列
Abstract: Signal-Clutter-Ratio (SCR) in reference channel is an important parameter for the evaluation of integration loss of passive radar. When PN sequence in the Digital Terrestrial Television Broadcast (DTTB) illuminator is utilized for SCR estimation, there will be the problem of fractional-delay received signal relative to local PN sequence, which leads to a severe deviation of SCR estimation. For this problem, a novel algorithm based on compressive sensing is proposed by exploiting the sparsity of signal in delay dimension. Simulation demonstrates that accurate estimation of delay and strength for signals of different strength can be obtained by the proposed algorithm, which ensures the accuracy of SCR estimation. The processing of experimental data shows that the whole SCR in the received data is relatively high and the integration loss is trivial, about 0.5 dB. In addition, SCR decreases with the length of baseline, which leads to the increase of integration loss.
- Passive radar /
- Compressive Sensing (CS) /
- Reference signal /
- Signal-Clutter-Ratio (SCR) /
- Fractional-delay /
- PN sequence

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