Joint estimation of frequency and DOA with spatio-temporal under sampling

Xiang-dong HUANG; Hong-yu XIAN; Zi-yang YAN; Sen-xue JING

doi:10.11959/j.issn.1000-436x.2016088

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Joint estimation of frequency and DOA with spatio-temporal under sampling

Papers | 更新时间：2024-06-05

- Joint estimation of frequency and DOA with spatio-temporal under sampling
- Journal on Communications Vol. 37, Issue 5, Pages: 21-28(2016)
- 作者机构：
  
  天津大学电子信息工程学院，天津300072
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61271322)
- DOI：10.11959/j.issn.1000-436x.2016088
  CLC： TN911.7
- Online First：2016-05，
  
  Published：15 May 2016
- 稿件说明：
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Xiang-dong HUANG, Hong-yu XIAN, Zi-yang YAN, et al. Joint estimation of frequency and DOA with spatio-temporal under sampling[J]. Journal on Communications, 2016, 37(5): 21-28.
DOI：

Xiang-dong HUANG, Hong-yu XIAN, Zi-yang YAN, et al. Joint estimation of frequency and DOA with spatio-temporal under sampling[J]. Journal on Communications, 2016, 37(5): 21-28. DOI： 10.11959/j.issn.1000-436x.2016088.

摘要

针对时—空欠采样下入射信号的频率和波达方向(DOA)估计问题，提出基于谱校正和中国余数定理的联合估计算法。首先利用稀疏分布的传感器阵元构造非均匀线阵，然后对入射信号做多路并行欠采样；借助AM估计器，该算法仅耗费少量样本即可获得精确频率和相位差余数，再结合闭式中国余数定理分别得到频率和DOA估计值。由于谱校正结果可以同时为频率估计器和DOA估计器所利用，因而该算法的样本利用率高。此外，与现有基于中国余数定理的频率估计法相比，该估计器无需对源信号做多次欠采样，耗时更短，更适用于快速时变目标的估计。仿真结果验证了联合估计算法的有效性和高精度，而且该算法在低信噪比情况下亦可达到很高的成功检测率，具有广阔的应用前景。

Abstract

In order to estimate the frequency and DOA of an incident signal with sub-Nyquist spatio-temporal sampling

A novel joint estimation algorithm based on spectrum correction and Chinese remainder theorem(CRT)was proposed.Firstly

the incident signal was parallelly sampled at multiple sensors non-uniformly located in a sparse linear array.Then

AM spectrum corrector was employed to extract the rema of frequency and phase-difference from a small quantity of snapshots.Finally

implementing the close-form CRT on these remainders directly yields the estimates of frequency and DOA.In the proposed scheme

the spectrum corrector was shared by both the frequency estimator and the DOA es-timator

which contributed to a high utilization of the snapshots.Furthermore

compared to the existing CRT based esti-mators

the proposed estimator needs not to incorporate multiple times of temporal undersampling on a single sensor

which saves considerable time consumption and thus obtain high ability of tracking time-variant objects.Simulations verify the feasibility and the high-accuracy of the proposed joint estimator and further study shows that high reconstruc-tion probability can be realized even in low SNR cases

which present the vast potential for future development.

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references

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