As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardne...As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardness problem of matching association between target and measurement in the process of scouting to data-link, which has complicated technical architecture of network construction. In this paper, taking advantage of cooperation mechanism on signal level in the aviation multi-station sympathetic network, a method of obtaining target time difference of arrival (TDOA) measurement using multi-station collaborative detecting based on time-frequency association is proposed. The method can not only achieve matching between target and its measurement, but also obtain TDOA measurement by further evolutionary transaction through refreshing sequential pulse time of arrival (TOA) measurement matrix for matching and correlating. Simulation results show that the accuracy of TDOA measurement has significant superiority over TOA, and detection probability of false TDOA measurement introduced by noise and fake measurement can be reduced effectively.展开更多
针对想定战场中机间数据链网络通信模型的上行链路功率控制问题,采用了一种基于多目标灰狼算法(Multi-objective Grey Wolf Optimizer,MOGWO)的功率控制方法。将功率控制建模为多目标优化问题,以最小化上行链路中各节点功率、使各节点...针对想定战场中机间数据链网络通信模型的上行链路功率控制问题,采用了一种基于多目标灰狼算法(Multi-objective Grey Wolf Optimizer,MOGWO)的功率控制方法。将功率控制建模为多目标优化问题,以最小化上行链路中各节点功率、使各节点在接收机处的信干噪比值(Signal-to-Interference plus Noise Ratio,SINR)接近目标SINR和最小化通信时截获概率为多目标优化问题建立模型,利用MOGWO求解问题模型Pareto前沿,依据系统选解准则求得最佳解。结果表明,MOGWO、多目标粒子群算法、基于分解的多目标进化算法与多目标蚁狮算法所得解对应各节点SINR的平均标准偏差分别为0.0968、0.3544、1.0900和0.3083。在恒定功率方法下最远节点处SINR已不满足正常通信需求,验证了MOGWO功率控制方法有更好的稳定性与寻优能力。展开更多
基金supported by the National Natural Science Foundation of China(61472443)the Basic Research Priorities Program of Shaanxi Province Natural Science Foundation of China(2013JQ8042)
文摘As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardness problem of matching association between target and measurement in the process of scouting to data-link, which has complicated technical architecture of network construction. In this paper, taking advantage of cooperation mechanism on signal level in the aviation multi-station sympathetic network, a method of obtaining target time difference of arrival (TDOA) measurement using multi-station collaborative detecting based on time-frequency association is proposed. The method can not only achieve matching between target and its measurement, but also obtain TDOA measurement by further evolutionary transaction through refreshing sequential pulse time of arrival (TOA) measurement matrix for matching and correlating. Simulation results show that the accuracy of TDOA measurement has significant superiority over TOA, and detection probability of false TDOA measurement introduced by noise and fake measurement can be reduced effectively.
文摘针对想定战场中机间数据链网络通信模型的上行链路功率控制问题,采用了一种基于多目标灰狼算法(Multi-objective Grey Wolf Optimizer,MOGWO)的功率控制方法。将功率控制建模为多目标优化问题,以最小化上行链路中各节点功率、使各节点在接收机处的信干噪比值(Signal-to-Interference plus Noise Ratio,SINR)接近目标SINR和最小化通信时截获概率为多目标优化问题建立模型,利用MOGWO求解问题模型Pareto前沿,依据系统选解准则求得最佳解。结果表明,MOGWO、多目标粒子群算法、基于分解的多目标进化算法与多目标蚁狮算法所得解对应各节点SINR的平均标准偏差分别为0.0968、0.3544、1.0900和0.3083。在恒定功率方法下最远节点处SINR已不满足正常通信需求,验证了MOGWO功率控制方法有更好的稳定性与寻优能力。
