In wireless positioning system, in addition to channel error, the geometric re- lationship between sensor nodes and the target may also affect the positioning accuracy. The effect is called geometric dilution of precision (GDOP). GDOP is determined as ratio factor between location error and measurement error. A higher GDOP value indicates a larger location error in location estimation. Accordingly, the location performance will be poor. The GDOP can therefore be used as an in- dex of the positioning performance. In this thesis, approaches of tracking a moving target with extended Kalman filter (EKF) in a time-difference-of-arrival (TDOA) wireless positioning system are discussed. While the target changes its position with time, the geometric layout between sensor nodes and the target will become differ- ent. To maintain the good layout, the positioning system with mobile sensor nodes is considered. Therefore, the geometric layout can be possibly improved and GDOP effect can be reduced by the mobility of mobile sensor nodes. In order to find the positions that mobile sensor nodes should move to, a time-varying function based on the GDOP distribution is defined for finding the best solutions. Since the simu- lated annealing is capable of escaping local minima and finding the global minimum in an objective function, the simulated annealing algorithm is used in finding the best solutions in the defined function. Thus the best solutions can be determined as the destinations of mobile sensor nodes. When relocating mobile sensor nodes from their current positions to the destinations, they may pass through or stay in high GDOP regions before arriving at the destinations. To avoid the problem, we establish an objective function for path planning of mobile sensor nodes in order to minimize the overall positioning accuracy. Simulation results show that the mobile sensor nodes will accordingly change their positions while the target is moving. All the sensor nodes will maintain a surrounding region to localize the target and the GDOP effect can be effectively reduced.

Wireless sensor networks (WSNs) have been used in many applications by deploying tiny and stationary sensors. In recent years, a lot of studies proposed to introduce mobility capability to sensor nodes in order to exploit the advantages of mobility, particularly to restore connectivity in disjoint WSNs. While the studies demonstrated various capabilities of the proposed connectivity algorithms via simulation, real node and testbed implementations were mostly lacking due to unavailability of proper mobile nodes. Since this may hinder the direct applicability of the algorithms in realistic settings, testbeds which can be constructed with low-cost and commercial-off-the-shelf (COTS) hardware are required for realistic evaluations of the connectivity restoration algorithms. In this thesis, we design a low-cost mobile sensor node called iRobotSense, by integrating iRobot Create platform with IRIS sensor. Then, a mobile sensor network (MSN) testbed of iRobotSense nodes is used to implement and evaluate a widely used connectivity restoration algorithms, namely PADRA. Furthermore, all of the previous works exploiting mobility of the nodes to achieve recovery in a partitioned network have assumed reachability of the nodes to the selected destinations via a direct path movement. However, in real-world applications, such assumption makes the schemes impractical in case of encountering obstacles or intolerable terrains. Besides, even if direct path movement is successful, optimal energy efficiency cannot be attained by neglecting the elevation or friction of the terrain. Thus, in the recovery efforts, terrain type, elevation as well as the obstacles should be taken into account. In this thesis, we re-design an existing connectivity restoration approach in disjoint MSNs to fit these requirements and evaluate the performance issues when realistic terrains are assumed. Rather than following a direct path, movement trajectory is determined based on a path planning algorithm which considers the risk and elevation of terrain sections to be visited while avoiding obstacles and highly elevated terrain sections.