Small range localization using wireless ultrasound sensor network - Tan, Eric Wee Shan (2016)
In the past few years, technological advances in electronics have led to cost effective, power efficient and small Wireless Sensor Network (WSN). Many new techniques to localize mobile targets in indoor environment were investigated and there are a lot of other vast new systems that requires this tracking techniques. Object localization and tracking problems in WSNs have been capturing quite a lot of attention lately. Electronics future of precision had prompted the need to achieve higher localization accuracy, smallest form factor and lower cost price. Received Signal Strength (RSS) based localization techniques are the state-of-the-art tracking research type of applications. Another type of localization method, analytical localization, is also used and it involves the use of Triangulation and Trilateration. However, when ultrasound is introduced to the localization systems, noise was introduced and it can cause variations of the distance measurement readings from the sensors and renders the analytical localization methods to be producing inaccurate results. Thus, Kalman filter was then introduced as it is an iterative state estimator and is very useful in tracking objects with noisy measurements. The localization system will be carried out in two steps, namely distance measurement and localization. The first step is range measurement where the testing between a number of reference nodes and the target is carried out. The second step, localization, is the computation of the position of the mobile node based on the TOA-based ranging data.