Low-PowerWireless Sensor Network Platforms - Signal Processing Systems - page 400

7.1 Localization

Ubiquitous localization has been widely studied during the recent years. In general,
the solutions focus on finding effective location estimation algorithms and measure-
ments that correlate with location. Localization can be categorized to range-based,
proximity-based, and scene analysis [ 14 ] . The underlying technologies vary from
pure RF-based, to UltraSound (US), InfraRed (IR), and multimodal solutions.

7.1.1 Range-Based Localization

Range-based approaches rely on estimating distances between localized nodes
and anchor nodes, which know their locations a priori. This process is called
ranging. Received Signal Strength (RSS) is a common RF-based ranging technique.
Distances estimated using RSS can have large errors due to multipath signals
and shadowing caused by obstructions [ 37 ] . The inherent unreliability has to be
addressed in the used localization algorithms. In [ 24 ] , RSS is replaced with multiple
varying power level beacon transmissions.
Several location estimation techniques can be used in range-based localization.
Utilized methods include trilateration, weighted center of gravity calculation, and
Kalman filtering. Many mathematical optimization methods, such as the steepest
descent method, sum of errors minimization, and Minimum Mean Square Er-
ror (MMSE) method, have been used to solve range-based location estimation
problems.

7.1.2 Proximity-Based Localization

Proximity-based approaches exploiting RF signals [ 5 , 18 ] estimate locations from
connectivity information. Such solutions are also commonly referred to as range-
free in the literature.
In the strongest base station method [ 18 ] the localized node's location is
estimated to be the same as the location of the anchor node it is connected to.
In [ 5 ] , the unknown location is estimated using connectivity information to several
anchor nodes. Only a very coarse grained location can be estimated using the
strongest base station method. The solutions presented in [ 5 ] improve the granularity
slightly. Nevertheless, in order to reach small granularities the connectivity-based
schemes require a very dense grid of anchor nodes. Their, strength is fairly simple
implementation and modest HW requirements.

7.1.3 Scene Analysis

Scene analysis consists of an off-line learning phase and an online localization
phase. The off-line phase includes recording RSS values corresponding to different