Title :
A Multiobjective Evolutionary Tracking Indoor Positioning Algorithm for Smart Space
Author :
Qin, Hang ; Du, Youfu
Author_Institution :
Comput. Sch., Yangtze Univ., Jingzhou
Abstract :
This paper is mainly devoted to identify an evolutionary approach based on search strategy, namely multiobjective evolutionary algorithm for indoor positioning (MEIP). Each subproblem is optimized by information from its several neighboring subproblems, which makes MEIP lower computational complexity at each generation and be capable of determining the user position with high accuracy. Experimental results have demonstrated that MEIP is able to achieve accuracy significantly better than the current WLAN location determination systems. It has been shown that MEIP using objective normalization can deal with disparately scaled objectives, and MEIP with an advanced decomposition method can generate a set of very evenly distributed solutions for n-objective test instances. The ability of MEIP to track a large number of users and to be used with large areas, the scalability and sensitivity of MEIP have also been experimentally investigated in this paper.
Keywords :
evolutionary computation; indoor radio; search problems; WLAN location determination system; computational complexity; indoor positioning algorithm; multiobjective evolutionary algorithm; multiobjective evolutionary tracking; search strategy; smart space; Design optimization; Evolutionary computation; Fingerprint recognition; Genetics; Neural networks; Radar detection; Radar tracking; Testing; Ultrasonic imaging; Wireless LAN; Indoor positioning; Pareto optimality; evolutionary algorithm; fingerprint; multiobjective optimization;
Conference_Titel :
Genetic and Evolutionary Computing, 2008. WGEC '08. Second International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-0-7695-3334-6
DOI :
10.1109/WGEC.2008.13