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A wireless sensor network (WSN) consists of sensor nodes (SNs) with wireless communication capabilities for specific sensing tasks. Among different applications, wireless location technologies which are designated to estimate the position of SNs (Geziciet al., 2005) (Haraet al., 2005) (Patwari et al., 2005)have drawn a lot of attention over the past few decades. There are increasing demands for commercial applications to adopt location tracking information within their system design, such as navigation systems, location-based billing, health care systems, and intelligent transportation systems. With emergent interests in location-based services (Perusco & Michael, 2007), location estimation and tracking algorithms with enhanced precision become necessitate for the applications under different circumstances. The location estimation schemes have been widely proposed and employed in the wireless communication system. These schemes locate the position of a mobile sensor (MS) based on the measured radio signals from its neighborhood anchor nodes (ANs). The representative algorithms for the measured distance techniques are the Time-Of-Arrival (TOA),the Time Difference-Of-Arrival (TDOA), and the Angle-Of-Arrival (AOA). The TOA scheme measures the arrival time of the radio signals coming from different wireless BSs; while the TDOA scheme measures the time difference between the radio signals. The AOA technique is conducted within the BS by observing the arriving angle of the signals coming from the MS. It is recognized that the equations associated with the location estimation schemes are inherently nonlinear. The uncertainties induced by the measurement noises make it more difficult to acquire the estimated MS position with tolerable precision. The Taylor Series Expansion (TSE) method was utilized in(Foy, 1976) to acquire the location estimation of the MS from the TOA measurements. The method requires iterative processes to obtain the location estimate from a linearized system. The major drawback of the TSE scheme is that it may suffer from the convergence problem due to an incorrect initial guess of the MS’s position. The two-step Least Square (LS) method was adopted to solve the location estimation problem from the TOA (Wanget al., 2003), the TDOA (Chen& Ho, 1994), and the hybrid TOA/TDOA(Tseng & Feng, 2009) measurements. It is an approximate 12

Mobile Location Tracking Scheme for Wireless Sensor Networks with Deficient Number of Sensor Nodes