In this paper, a chaos system and proportional differential control are both used to detect the frequency of an unknown signal. In traditional methods the useful signal is obtained through the Duffing equation or othe...In this paper, a chaos system and proportional differential control are both used to detect the frequency of an unknown signal. In traditional methods the useful signal is obtained through the Duffing equation or other chaotic oscillators. But these methods are too complex because of using a lot of chaos oscillators. In this paper a new method is presented that uses the Rossler equation and proportional differential control to detect a weak signal frequency. Substituting the detected signal frequency into the RSssler equation leads the Rossler phase state to be considerably changed. The chaos state can be controlled through the proportional differential method. Through its phase diagram and spectrum analysis, the unknown frequency is obtained. The simulation results verify that the presented method is feasible and that the detection accuracy is higher than those of other methods.展开更多
In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user syste...In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.展开更多
无人机协同目标感知技术是有人机无人机混合运行的重要安全保障.针对复杂空域环境下的感知可靠性问题,分析大中型无人机的复杂融合空域运行场景,并确定无人机协同目标感知的精准性、高实时性、抗干扰性和低载荷性等需求,提出一种四单元...无人机协同目标感知技术是有人机无人机混合运行的重要安全保障.针对复杂空域环境下的感知可靠性问题,分析大中型无人机的复杂融合空域运行场景,并确定无人机协同目标感知的精准性、高实时性、抗干扰性和低载荷性等需求,提出一种四单元阵列天线和数字化射频体制的无人机协同目标感知系统架构;同时,结合空管雷达信号特性和天线体制,设计方位感知算法,通过修正协方差矩阵、信号子空间加权和噪声子空间加权等方法,设计基于多信号分类(multiple signal classification,MUSIC)的空间谱估计算法,并提出基于子空间分解的幅相误差在线估计算法;最后,开展算法仿真试验和实际空域环境飞行试验.研究结果表明:相比传统MUSIC算法,优化算法的方位感知高分辨性能提升23.3%,并改善了无人机协同目标方位感知的高实时性、抗干扰性和低载荷性.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No. 60877065)Science and Technology Innovation Talents Special Funds of Harbin,China (Grant No. RC2008XK009004)the Heilongjiang Provincial Education Department,China (Grant No. 11544035)
文摘In this paper, a chaos system and proportional differential control are both used to detect the frequency of an unknown signal. In traditional methods the useful signal is obtained through the Duffing equation or other chaotic oscillators. But these methods are too complex because of using a lot of chaos oscillators. In this paper a new method is presented that uses the Rossler equation and proportional differential control to detect a weak signal frequency. Substituting the detected signal frequency into the RSssler equation leads the Rossler phase state to be considerably changed. The chaos state can be controlled through the proportional differential method. Through its phase diagram and spectrum analysis, the unknown frequency is obtained. The simulation results verify that the presented method is feasible and that the detection accuracy is higher than those of other methods.
基金supported in part by the National Natural Science Foundation of China for Young Scholars under Grant No.61701167Young Elite Backbone Teachers in Blue and Blue Project of Jiangsu Province, China
文摘In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.
文摘无人机协同目标感知技术是有人机无人机混合运行的重要安全保障.针对复杂空域环境下的感知可靠性问题,分析大中型无人机的复杂融合空域运行场景,并确定无人机协同目标感知的精准性、高实时性、抗干扰性和低载荷性等需求,提出一种四单元阵列天线和数字化射频体制的无人机协同目标感知系统架构;同时,结合空管雷达信号特性和天线体制,设计方位感知算法,通过修正协方差矩阵、信号子空间加权和噪声子空间加权等方法,设计基于多信号分类(multiple signal classification,MUSIC)的空间谱估计算法,并提出基于子空间分解的幅相误差在线估计算法;最后,开展算法仿真试验和实际空域环境飞行试验.研究结果表明:相比传统MUSIC算法,优化算法的方位感知高分辨性能提升23.3%,并改善了无人机协同目标方位感知的高实时性、抗干扰性和低载荷性.
