Fast and High Precision Multi-target Positioning via Imaging Strategy

ZHANG Xiaoling; YU Lei; WU Xiliang; HE Shufeng

doi:10.11999/JEIT151315

Volume 38 Issue 9

Sep. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(9): 2330-2335

ZHANG Xiaoling, YU Lei, WU Xiliang, HE Shufeng. Fast and High Precision Multi-target Positioning via Imaging Strategy[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2330-2335. doi: 10.11999/JEIT151315

Citation:

ZHANG Xiaoling, YU Lei, WU Xiliang, HE Shufeng. Fast and High Precision Multi-target Positioning via Imaging Strategy[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2330-2335. doi: 10.11999/JEIT151315

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Fast and High Precision Multi-target Positioning via Imaging Strategy

doi: 10.11999/JEIT151315

Funds:

Aeronautical Science Foundation of China (20130180001, 20142080007)

Received Date: 2015-11-25
Rev Recd Date: 2016-04-13
Publish Date: 2016-09-19

Abstract

Abstract

The association between multiple targets and echo data is the main problem for multi-target location method, which causes huge calculation and the problem of extracting the targets accurately. The location method based on Bistatic Range Space Projection (BRSP) can be used for the sake of overcoming the data association problem. While there are two problems existing on the location method of BRSP, the huge calculation and the low resolution. In the face of vast calculation in projection imaging localization, this paper utilizes hierarchical strategy to decrease calculation. The possible targets areas are located with low resolution at first. After that, more precision probable areas are pinpointed via higher resolution from these possible areas. In this way, the calculation of areas without targets can be avoided. Furthermore, results of hierarchical processing are used to be the initial position guess for Taylor-series estimation. Positioning errors could be modified by the iterative correction of Taylor-series estimation. Simulation results indicate a significant improvement in the running time and positioning precision of the proposed method.
- Sensor network,
- Data association,
- Imaging strategy,
- Hierarchical strategy,
- Taylor series expansion algorithm

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References(17)

References

HONG Shen, ZHI Ding, SOURA D, et al. Multiple source localization in wireless sensor networks based on time of arrival measurement[J]. IEEE Transactions on Signal Processing, 2014, 62(8): 1938-1949. doi: 10.1109/TSP.2014. 2304433.

CHAN Y T, HANG H, and CHING P C. Exact and approximate maximum likelihood localization algorithms[J]. IEEE Transactions on Vehicular Technology, 2006, 55(1): 10-16. doi: 10.1109/TVT.2005.861162.

SCHMIDT R O. Multiple emitter location and signal parameter estimation[J]. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 276-280. doi: 10.1109/TAP. 1986.1143830.

MENG Wei, XIE Linghua, and XIAO Wendong. Decentralized TDOA sensor pairing in multihop wireless sensor networks[J]. IEEE Signal Processing Letters, 2013, 20(2): 181-184. doi: 10.1109/LSP.2013.2237823.

XIONG Hui, CHEN Zhiyuan, YANG Beiya, et al. TDOA localization algorithm with compensation of clock offset for wireless sensor networks[J]. China Communications, 2015, 12(10): 193-201. doi: 10.1109/CC.2015.7315070.

NARESH V, STEVEN K, and QUAN Ding. TDOA based direct positioning maximum likelihood estimator and the cramer-rao bound[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(3): 1616-1635. doi: 10.1109/ TAES.2013.110499.

ZHU Guohui and FENG Dazheng. Bi-iterative method for moving source localisation using TDOA and FDOA[J]. Electronics Letters, 2015, 55(1): 8-10. doi: 10.1049/el.2014. 2386.

MOHAMMAD P and MARK L F. Distributed computation for direct position determination emitter location[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(4): 2878-2889. doi: 10.1109/TAES.2014.130005.

YANG Kehu and LUO Zhiquan. Robust target localization with multiple sensors using time difference of arrivals[C]. IEEE Radar Conference, Rome, 2008: 1080-1085. doi: 10.1109/RADAR.2008.4720928.

房嘉奇, 冯大政, 李进. 稳健收敛的时差频差定位技术[J]. 电子与信息学报, 2015, 37(4): 798-803. doi: 10.11999/JEIT 140560.

FANG Jiaqi, FENG Dazheng, and LI Jin. A robustly convergent algorithm for source localization using time difference of arrival and frequency difference of arrival[J]. Journal of Electronics Information Technology, 2015, 37(4): 798-803. doi: 10.11999/JEIT140560.

SHI Tongyan, ZHANG Xiaoling, and SHI Jun. Multi-target positioning for sensor network based on imaging strategy[C]. International Conference on Computational Problem- Solving, Jiuzhai, 2013: 171-174. doi: 10.1109/ICCPS.2013. 6893549.

SHI Jun, FAN Ling, ZHANG Xiao-ling, et al. Multi-target positioning for passive sensor network via bistatic range space projection[J]. SCIENCE CHINA Information Sciences, 2016, 59(1): 1-3 doi: 10.1007/s11432-015-5464-x.

HONG I K, CHUNG S T, KIM H K, et al. Fast forward and backward projection algorithm using SIMD[C]. Nuclear Science Symposium Conference Record, San Diego, 2006: 3361-3368. doi: 10.1109/NSSMIC.2006.353723.

SHI Jun, ZHANG Xiaoling, YANG Jianyu, et al. APC trajectory design for one-active linear-array three- dimensional imaging SAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(3): 1470-1486. doi: 10.1109/TGRS.2009.2031430.

WADE H F. Position-location solutions by Taylor series estimation[J]. IEEE Transactions on Aerospace and Electronic Systems, 1976, 12(2): 187-194. doi: 10.1109/ TAES.1976.308294.

CHAN Y T and HO K C. A simple and efficient estimator for hyperbolic location[J]. IEEE Transactions on Signal Processing, 1994, 42(8): 1905-1915. doi: 10.1109/78.301830.

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