In this paper, a joint adaptive sampling interval and power allocation (JASIPA) scheme based on chance-constraint programming (CCP) is proposed for maneuvering target tracking (MTT) in a multiple opportunistic array radar (OAR) system. In order to conveniently predict the maneuvering target state of the next sampling instant, the best-fitting Gaussian (BFG) approximation is introduced and used to replace the multimodal prior target probability density function (PDF) at each time step. Since the mean and covariance of the BFG approximation can be computed by a recursive formula, we can utilize an existing Riccati-like recursion to accomplish effective resource allocation. The prior Cramér-Rao lower boundary (prior CRLB-like) is compared with the upper boundary of the desired tracking error range to determine the adaptive sampling interval, and the Bayesian CRLB-like (BCRLB-like) gives a criterion used for measuring power allocation. In addition, considering the randomness of target radar cross section (RCS), we adopt the CCP to package the deterministic resource management model, which minimizes the total transmitted power by effective resource allocation. Lastly, the stochastic simulation is embedded into a genetic algorithm (GA) to produce a hybrid intelligent optimization algorithm (HIOA) to solve the CCP optimization problem. Simulation results show that the global performance of the radar system can be improved effectively by the resource allocation scheme.
It is believed that Internet of Things (IOT) is leading the third wave of IT revolution. In this paper, from the point of course construction system in university for Internet of Things major, its experimental system is studied deeply. The training project for this major must be established on the base of collaboration between colleges and enterprises of the industry background. By the talent training mode of cooperation between schools and enterprises, the joint research for application projects of Internet of Things are explored actively. An application project which is the construction for smart ancient city based on IOT is discussed in this paper. The architecture design is proposed.
Based on the research of ZigBee Network's present tree routing algorithm, this paper proposes a new tree routing algorithm based on neighbor table NTRA .The improved algorithm details a new method of counting the routing hops from the neighbor node to the destination node, and establishes a neighbor node selection strategy. The residual energy of nodes being considered, the routing selection is designed to keep away from those nodes with low residual energy so as to realize the local optimization. Besides, the NTRA algorithm saves energy consumption by solving the problem of big hop caused by the existing routing algorithms, which passes the simulation verification at last.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.