一个改进的双阶段稀有算法用于混合远场和近场源定位在未知的相互合下与统一的线性传感器阵列.
Keyu Chen1, Ke Deng1, Jianguo Zhang1
1Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
ITS-RARE算法准确地定位混合远场和近场源,即使是未知的相互合. 这种新的方法可以提高源分类和估计准确度,同时减少计算负载.
科学领域:
- 信号处理 信号处理
- 阵列信号处理 阵列信号处理
- 电磁学 电磁学 电磁学 电磁学
背景情况:
- 准确的源代码定位在各种应用中至关重要.
- 现有的方法与混合远场/近场源和未知的相互合作斗争.
- 相互合显著降低了阵列性能.
研究的目的:
- 提出一个改进的两阶段降级算法 (ITS-RARE).
- 为了能够在没有预校准的情况下共同估计远场 (FF) 源 DOA 和相互合因子.
- 为了实现近场源 (NFS) 的封闭形式范围估计,并减少计算复杂性.
主要方法:
- 为了确定相互合系数,利用排名缩小的自身向量.
- 联合估计FF源DOA和相互合因子.
- 同变矩阵重建 (CMR) 在FF/NF源分类过程中保持全阵列光圈.
- 对于NFS的封闭式范围估计.
主要成果:
- 成功实现了FF源DOA和相互合因子的联合估计.
- 启用了对NFS的准确封闭形式范围估计.
- 与现有的算法相比,显著降低了计算复杂性.
- 保留了全阵列光圈,提高了估计准确度.
结论:
- ITS-RARE算法提供了一个计算高效和有效的解决方案,用于定位混合FF/NF源.
- 该方法在处理未知的相互合时准确估计DOA和范围.
- 保持有效的阵列光圈导致更好的定位精度.
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