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Volume 23 Issue 4
 
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Article Navigation >  Journal of Unmanned Undersea Systems  > 2015  >  23(4): 269-275
YAN Zheng-tong, XIAO Su-juan, BAI Zhi-ke, CHEN Ya-lin. Receive-Transmit Coupling Interference Suppression for Torpedo Electro-magnetic Fuze Target Simulation System Based on Adaptive Cancellation[J]. Journal of Unmanned Undersea Systems, 2015, 23(4): 269-275. doi: 10.11993/j.issn.1673-1948.2015.04.004
Citation: YAN Zheng-tong, XIAO Su-juan, BAI Zhi-ke, CHEN Ya-lin. Receive-Transmit Coupling Interference Suppression for Torpedo Electro-magnetic Fuze Target Simulation System Based on Adaptive Cancellation[J]. Journal of Unmanned Undersea Systems, 2015, 23(4): 269-275. doi: 10.11993/j.issn.1673-1948.2015.04.004
shu

Receive-Transmit Coupling Interference Suppression for Torpedo Electro-magnetic Fuze Target Simulation System Based on Adaptive Cancellation

doi: 10.11993/j.issn.1673-1948.2015.04.004
  • 1.

    The 705 Research Institute, China Shipbuilding Industry Corporation, Xi′an 710075, China

  • 2.

    Science and Technology on Underwater Information and Control Laboratory, Xi′an 710075, China

  • Received Date: 2015-04-08
  • Rev Recd Date: 2015-04-20
  • Publish Date: 2015-08-20
    Abstract
  • Considering the importance of receive-transmit coupling interference suppression problem in simultaneous transmit-receive operation for the target echo simulation system, a coupling model of torpedo electromagnetic fuze for target echo simulation system is established in the condition of simultaneous transmit-receive operation. An adaptive cancellation algorithm is proposed to achieve real-time separation of target signal and coupling interference. The model and algorithm are analyzed via simulation and calculation, laying emphasis on the influence of parameters selection for the adaptive cancellation algorithm on the performance of coupling interference suppression. Simulation results show that the coupling interference suppression could be solved by the proposed algorithm if the parameters are selected properly. With respect to real-time property and stability of adaptive cancellation, the recursive least squares algorithm behaves better than the least mean square algorithm.

     

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