Double Threshold CFAR Detection for Multisite Radar

HU Qinzhen; SU Hongtao; ZHOU Shenghua; LIU Ziwei

doi:10.11999/JEIT151163

Volume 38 Issue 10

Oct. 2016

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HU Qinzhen, SU Hongtao, ZHOU Shenghua, LIU Ziwei. Double Threshold CFAR Detection for Multisite Radar[J]. Journal of Electronics & Information Technology, 2016, 38(10): 2430-2436. doi: 10.11999/JEIT151163

Citation:

HU Qinzhen, SU Hongtao, ZHOU Shenghua, LIU Ziwei. Double Threshold CFAR Detection for Multisite Radar[J]. Journal of Electronics & Information Technology, 2016, 38(10): 2430-2436. doi: 10.11999/JEIT151163

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Double Threshold CFAR Detection for Multisite Radar

doi: 10.11999/JEIT151163

Funds:

The National Natural Science Foundation of China (61372134, 61401329)

Received Date: 2015-10-21
Rev Recd Date: 2016-07-08
Publish Date: 2016-10-19

Abstract

Abstract

For multisite radar system, to solve the data transmission rate problem, two kinds of Double Threshold Constant False Alarm Rate (DT-CFAR) detectors, the DT Generalized Likelihood Ratio Test (DT-GLRT) detector and the DT Adaptive Matched Filter (DT-AMF) detector, are proposed based on the GLRT and the AMF algorithms. Fisrt, the local test statistics which exceed the first threshold are transferred to the fusion center. Then, the global test statistic is obtained from the local test statistics and the final decision is made compared to the second threshold in the fusion center. The closed form expression for probabilities of false alarm and detection of the DT-AMF detector are also given when the Signal to Clutter plus Noise Ratios (SCNRs) are identical in the spatial diversity channels. Simulation results illustrate that the DT-CFAR detectors can maintain a good performance with a low communication rate.
- Radar,
- Double hreshold detection,
- Constant False Alarm Rate (CFAR),
- Generalized Likelihood Ratio Test (GLRT),
- Adaptive Matched Filter (AMF)

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References(19)

References

HAIMOVICH A, BLUM R, CIMINI L, et al. MIMO radar with widely separated antennas[J]. IEEE Signal Processing Magazine, 2008, 25(1): 116-129. doi: 10. 1109/MSP.2008. 4408448.

ZHOU S H and LIU H W. Space-partition-based target detection for distributed MIMO radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(4): 2717-2729. doi: 10.1109/TAES.2013.6621848.

XU G, ZHU S Y, and CHEN B. Decentralized data reduction with quantization constraints[J]. IEEE Transactions on Signal Processing, 2014, 62(7): 1775-1784. doi: 10.1109/TSP. 2014.2303432.

GAO F, GUO L L, LI H B, et al. Quantizer design for distributed GLRT detection of weak signal in wireless sensor networks[J]. IEEE Transactions on Wireless Communications, 2015, 14(4): 2032-2042. doi: 10.1109/TWC. 2014.2379279.

BARKAT M and VARSHENY P. Decentralized CFAR signal detection[J]. IEEE Transactons on Aerospace and Electronic Systems, 1989, 25(2): 141-149. doi: 10.1109/7.18676.

KAILKHURA B, BRAHMA S, HAN Y S, et al. Distributed detection in tree topologies with byzantines[J]. IEEE Transactions on Signal Processing, 2014, 62(12): 3208-3219. doi: 10.1109/TSP.2014.2321735.

RAGO C, WILLETT P, and BAR-SHALOM Y. Censoring sensors: a low-communication-rate scheme for distributed detection[J]. IEEE Transactions on Aerospace and Electronic Systems, 1996, 32(2): 554-568. doi: 10.1109/7.489500.

APPADWEDULA S, VEERAVALLI V, and JONES D. Decentralized detection with censoring sensors[J]. IEEE Transactions on Signal Processing, 2008, 56(4): 1362-1373. doi: 10.1109/TSP.2007.909355.

GUL G and ZOUBIR M. Robust detection under communication constraints[C]. IEEE 14th Workshop on Signal Processing Advances in Wireless Communications, Darmstadt, 2013: 410-414. doi: 10.1109/SPAWC.2013. 6612082.

HE H and VARSHNEY P. Distributed detection with censoring sensors under dependent observations[C]. IEEE International Conference on Acoustic, Speech and Signal Processing, Florence, 2014: 5055-5059. doi: 10.1109/ICASSP. 2014.6854565.

HE Q, Blum R, and RAWAS Z. Ordering for energy efficient communications for noncoherent MIMO radar networks[C]. IEEE International Conference on Acoustic, Speech and Signal Processing, Kyoto, 2012: 5189-5192. doi: 10.1109/ ICASSP.2012.6289089.

SCHARRENBROICH M, ZATMAN M, and BALAN R. Cooperative radar techniques: the two-step detector[C]. Conference Record of the 45th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, 2011: 1975-1979. doi: 10.1109/ACSSC.2011.6190370.

SCHARRENBROICH M, ZATMAN M, and BALAN R. Performance of a practical two-step detector for non- fluctuating targets[C]. IEEE 7th Workshop on Sensor Array and Multichannel Signal Processing, Hoboken, 2012: 313-316. doi: 10.1109/SAM.2012.6250498.

KELLY E. An adaptive detection algorithm[J]. IEEE Transactions on Aerospace and Electronic Systems, 1986, 22(1): 115-127. doi: 10.1109/TAES.1986.310745.

ROBEY F, FUHRMANN D, KELLY E, et al. A CFAR adaptive matched filter detector[J]. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28(1): 208-216. doi: 10.1109/7.135446.

CHRISTIAN W. Hand-book on Statistical Distributions for Experimentalists[M]. Stockholm: University of Stockholm, 2007: 133-133.

RAMSAY C M. The distribution of sums of certain I.I.D Pareto variates[J]. Communications in Statistics-Theory and Methods, 2006, 35(1): 395-405. doi: 10.1080/03610920500 476325.

MATHUR A and WILLETT P K. Local SNR consideration in decentralized CFAR detection[J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(1): 13-22. doi: 10.1109/7.640257.

DONALD P B and NATHAN A G. Adaptive detection and diversity order in multistatic radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 2008, 44(4): 1615-1623. doi: 10.1109/TAES.2008.4667736.

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