Localisation

Abstract

Most wireless sensor network applications require knowing or measuring locations of thousands of sensors accurately. In environmental sensing applications such as bush fire surveillance, water quality monitoring and precision agriculture, for example, sensing data without knowing the sensor location is meaningless (Patwari et at. 2003). In addition, location estimation may enable applications such as inventory management, intrusion detection, road traffic monitoring, health monitoring, etc. Sensor network localisation refers to the process of estimating the locations of sensors using measurements between neighbouring sensors such as distance measurements and bearing measurements. In sensor network localisation, it is typically assumed that small portions of sensors, called anchors, have a priori information about their coordinates. These anchor nodes serve to fix the location of the sensor network in the global coordinate system. In applications, which do not require a global coordinate system (e.g., monitoring in an office building or home environment), these anchor nodes define the reference coordinate system in which all other sensors are referred to. The coordinates of the anchor nodes may be obtained by using a global positioning system (GPS) or by installing the anchor nodes at fixed points with known coordinates. However due to constraints on cost and size of sensors, energy, implementation environment (e.g., GPS receivers cannot detect the satellites transmission indoors) or the deployment of sensors (e.g., sensor nodes may be randomly deployed in the region), most sensors do not have a priori coordinate information. These sensor nodes without a priori coordinate information are referred to as the non-anchor nodes and their coordinates are to be estimated by the sensor network localisation algorithm. In this chapter, we shall provide an overview of sensor network localisation techniques as well as an introduction to the fundamental theory underpinning the sensor network localisation. While many techniques covered in this chapter can be applied in both 2- dimensions (ℝ 2 ) and 3-dimensions (ℝ 3 ), we choose to focus on 2-dimensional localisation problems. The rest of the chapter is organised as follows. In Section 2, we shall provide an overview of measurement techniques and the corresponding localisation algorithms. In Section 3 we shall focus on connectivity-based localisation algorithms. In Section 4 we shall focus on distance-based localisation techniques. Section 5 introduces the fundamental theory of the various distance-based localisation techniques and Section 6 summarises current research problems in distance-based localisation. Finally a summary is provided in Section 7. Show more