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Volume 19 Issue 3
May  1997
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Que Weiyan, Peng Yingning, Lu Dajin, Hou Xiuying . ANALYSIS OF DATA FUSION ALGORITHMS FOR DETECTION PROBLEM[J]. Journal of Electronics & Information Technology, 1997, 19(3): 393-402.
Citation: Que Weiyan, Peng Yingning, Lu Dajin, Hou Xiuying . ANALYSIS OF DATA FUSION ALGORITHMS FOR DETECTION PROBLEM[J]. Journal of Electronics & Information Technology, 1997, 19(3): 393-402.

ANALYSIS OF DATA FUSION ALGORITHMS FOR DETECTION PROBLEM

  • Received Date: 1996-06-16
  • Rev Recd Date: 1996-11-14
  • Publish Date: 1997-05-19
  • In recent years, the radar network systems for modern military application, such as anti-stealth tactical and strategic surveillance systems, have been investigated with great interest, and multisensor data fusion has been a hot issue. Consequently, the critical need is to understand it in concept and application and provide a common frame of reference for detection data fusion algorithms. To fill that need, in this paper, the relation between the multisensor detection problem and classical detection problem is pointed out. Discrimination information is used to analyze and compare, in principle, the various representative data fusion algorithms for detection that appeared in some open literatures, and the other possible algorithms are proposed as well. The effects of data fusion on surveillance systems are discussed with some numerical results, and it is shown that data fusion technique is of great importance to anti-stealth systems.
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  • Waltz E, Llina J. Multisensor Data Fusion. Boston: Artech House, 1990, Charpter 1-12.[2]Blahut R E. Principles and Practice of Information Theory. Sydney: Addison-Wesley Publishing Company, 1987, Charpter 4.[3]Kailath T. The divergence and Bhattacharyya distance measure in signal selection. IEEE Trans. on COM, 1967, COM-15(1): 52-60.[4]Bahert W F. The beginning of stealth technology. IEEE Trans. on AES, 1993, AES-29(4): 1376-1385.[5]Srinivasan R. Distributed radar detection theory. IEE Proc: F,1986,133 (1)55-60.[6]Volstrom C W. Gradient algorithm for quantization levels in distributed detection systems. IEEE Trans. on AES, 1995, AES-31(1): 390-398.[7]Chair Z. Optimal data fusion in multiple sensor detection system. IEEE Trans. on AES, 1986, AES-22(1): 98-101.[8]Sadjadi F A. Hypotheses testing in a distributed environment. IEEE Trans. on AES, 1986, AES-22(2): 134-137.[9]Reibman A R. Optimal detection and performance of distributed sensor system. IEEE Trans. on AES, 1987, AES-23(1): 24-30.[10]Thomopoulos S C A. Optimal decision fusion in multiple sensor system. IEEE Trans. on AES,1987, AES-23(5): 644-653.[11]Lee C C. Optimal local decision space partitioning for distributed detection. IEEE Trans. on AES, 1989, AES-25(4): 536-544.[12]Tao Li. Optimal multiple level decision fusion with distributed sensors. IEEE Trans. on AES, 1989, AES-29(4): 1252-1259.[13]Thomopoulos S C A, Bougonlias D K, Wann C D. Dignet: An unsupervised-learning clustering algorithm for clustering and data fusion. IEEE Trans. on AES, 1995, AES-31(1): 21-38.[14]Jun Han. Distributed binary integration. IEEE Trans. on AES, 1993, AES-29(1): 2-8.[15]Papastavrou J D. Distributed detection by a large team of sensors in tandem. IEEE Trans. on AES, 1992, AES-28(3): 639-652.[16]Viswanathan R. Optimal serial distributed decision fusion. IEEE Trans. on AES, 1988, AES-24(4): 366-376.[17]Swaszek P F. On the performance of serial networks in distributed detection. IEEE Trans. on AES, 1992, AES-29(1): 254-259.[18]Veeravalli V V, Briar T, Poor H V. Decentralized sequential detection with a fusion center performing the sequential test. IEEE Trans. on IT, 1993, IT-39(2): 433-442.[19]Geraniotis E, Chau Y A. Robust data fusion for multisenaor detection systems. IEEE Trans. on IT, 1990, IT-36(6): 1265-1279.[20]Alhakeem S, Vershney P K. A unified approach to the design of decentralized detection systems. IEEE Trans. on AES, 1995, AES-31(1): 9-20.[21]Swaszek P F, Willett P. Parley as an approach to distributed detection. IEEE Trans. on AES, 1995, AES-31(1) : 446-457.[22]Klein L A. A Boolean algebra appoach to multiple seneor voting fusion. IEEE Trans. on AES, 1993, AES-29(2): 317-327.[23]Klein L A. Processing requirements for multisensor low-cost brilliant munitions, IEEE Trans. on AES, 1993, AES-29(4): 1084-1094.[24](due W, Peng Y, Lu D, Hou X. An approach to radar netting. 1996 CIE International Conference of Radar Proceedings, Beijing: 1996, IEEE Press, 1996, 573-577.
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