Modeling and Optimizing Positional Accuracy Based on Hyperbolic Geometry for the Adaptive Radio Interferometric Positioning System

Abstract

Abstract.One of the most important performance objectives for a localization system is positional accuracy. It is fundamental and essential to general location-aware services. The radio interferometric positioning (RIP) method [1] is an exciting approach which promises sub-meter positional accuracy. In this work, we would like to enhance the RIP method by dynamically selecting the best anchor nodes as beacon senders, and further optimizing the positional accuracy when tracking multiple targets. We have developed an estimation error model to predict positional error of the RIP algorithm given different combinations of beacon senders. Building upon this estimation error model, we further devise an adaptive RIP method that selects the optimal sender-pair combination (SPC) according to the locations of targets relative to anchor nodes. We have implemented the adaptive RIP method and conducted experiments in a real sensor network testbed. Experimental results have shown that our adaptive RIP method outperforms the static RIP method in both single-target and multi-target tracking, and improves the average positional accuracy by 47%~60% and reduces the 90% percentile error by 55%~61%.

Stochastic radio interferometric positioning in the 2.4 GHz range

“…We numerically determine the value of W as 12.5 centimeters. We rewrite Equation 13 with the aid of Equation 14 as: Figure 7 shows an example of the smoothed t-range error distribution using Equation 14. Figure 8 shows this smoothed t-range error distribution over the localization surface using Equation 15.…”

“…This latter cost function calculates the position by minimizing the squared difference between the calculated and estimated q-ranges. RIPS ( [8], [12] and [14]) uses a Least Squares Method to calculate the position that best fits the measurements. In Radio Interferometric Positioning, the measured values are the phase offset measurements.…”

“…RIPS ( [8], [12] and [14]) estimates the position by sequentially minimizing two cost functions. First it calculates the q-ranges by minimizing the cost function described in Equation 8.…”

Spinning beacons for precise indoor localization

“…The RIPS measures the relative phase offset of the received interference signals to obtain q-range information, which is the linear combination of distances between the two radio transmitters and the two receivers. Wu et al [21] developed the adaptive RIPS that enhanced the positional accuracy of RIPS by dynamically selecting anchor nodes as beacon senders.…”

An Innovative Positioning System with Unsynchronized Interferometric Modulated Signals in Wireless Sensor Networks

“…10 Many efforts have been made to improve RIPS. 11,12,13,14,15 However, it is still difficult to implement RIPS algorithms on existing hardware:…”