In this paper,first,the optimality of GSS algorithm is discussed,and a theoretical analysis as well asseveral counter- examples is presented to prove that the traditional GSS algorithm does not guarantee the obtaining ofoptimal solution.Then,in the condition that the state vector dimension is larger than the observation vector dimen-sion,an improved GSS algorithm combining the exhaustive search is proposed to avoid the selection result degrada-tion due to the randomness of initial solution selection.Experimental results indicate that the improved algorithm iseffective in practice because it is of a high optimal selection rate of more than 90% and a low solution error of lessthan 0.35% even when the optimal selections are suboptimum.Moreover,the simulated results of the target track-ing in wireless sensor networks demonstrate that the improved GSS algorithm is superior to the traditional one.