欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
针对多假目标欺骗干扰下异地配置的主／被动雷达传感器系统，提出了一种新的三维情况下主／被动雷达联合鉴别虚假目标算法。首先采用基准线最小距离法排除部分虚假目标，再利用三维分配算法进一步进行鉴别。该算法与基于角度统计量和距离统计量鉴别虚假目标算法相比，可以得到较高的正确鉴别概率和较低的误鉴别概率。最后通过仿真的方法分析了观测次数、虚假目标距离和被动雷达精度对算法鉴别虚假目标概率的影响，结果表明，该算法可使主／被动雷达系统有效鉴别假目标。
英文摘要：
To reject multi-false-target deception jamming, a new data processing algorithm in three dimensions（3D） is proposed for active/passive radar at different sites. In the discrimination algorithm, datum line minimum distance algorithm is adopted to eliminate some false target, and 3D assignment al- gorithm is adopted to discriminate the active decoys. Compared with the discrimination algorithm based on angle statistics and the discrimination algorithm based on range statistics, the new discrimination algo- rithm can acquire higher correct discrimination probability and lower incorrect discrimination probability. Finally, the influence of observation frequency, the distance of active decoys and the passive radar accu- racy on algorithm＇ s discrimination probability are analyzed by using modeling methods. Simulation results show that active/passive radar can reject the false targets effectively by using this algorithm.
同期刊论文项目
同项目期刊论文
Joint systematic error estimation algorithm for radar and automatic dependent surveillance broadcast
Data Reduction with Quantization Constraints for Decentralized Estimation in Wireless Sensor Network
A New Noise-compensated Estimation Scheme for Multichannel Autoregressive Signals from Noisy Observa
Dual-Decomposition Approach for Distributed Optimization in Wireless Sensor Networks, Wireless Algor
Adaptive range-spread target detection based on modified generalised likelihood ratio test in non-Ga
Diffusion-based EM Algorithm for Distributed Estimation of Gaussian Mixtures in Wireless Sensor Netw
Robust Distributed Fusion for System with Randomly Uncertain Sensor Estimation Error Cross-Covarianc
位置：