Sensor localization using acoustic doppler shift with a mobile access point

Abstract

The nodes in a sensor network are often deployed in random locations. However, most applications require that the location and/or orientation of the nodes be known, so post-deployment algorithms for self-localization of the sensor nodes are important. We consider using a mobile access point (AP) for sensor node localization in a randomly deployed sensor network. We focus on the particular case in which the sensors measure the acoustic Doppler shift in a tone that is emitted from the mobile AP. In addition to the acoustic emission, the mobile AP broadcasts a radio signal that contains AP position, velocity, timing, and parameters of the acoustic signal. We demonstrate that atmospheric turbulence has a significant impact on the accuracy of sensor localization, degrading performance by as much as two orders of magnitude relative to an ideal, planewave propagation model. We present Cramer-Rao bounds (CRBs) for sensor localization accuracy and compare the performance of algorithms to the CRBs under "cloudy" and "sunny" weather conditions.

High Confidence Networked Control for Next Generation Air Transportation Systems

“…Rangebased techniques use distance estimates or angle estimates in location calculations, while range-free solutions depend only on the contents of received messages. Range-based approaches utilize time of arrival [11], time difference of arrival of two different signals [12], angle of arrival [13], RSS [14], and Doppler shifts [15], [16]. Some of these techniques require expensive separate hardware [11], [12], [13].…”

“…The range-based approach using Doppler shifts is less susceptible to multi-path propagation than the RSS-based ranging approach [14], [17], since reflections do not change the frequency of the signal. The Doppler effect has been used extensively to estimate the velocity of tracked objects or to improve the accuracy of tracking systems [15], [16]. In [15], the self-localization of sensors is developed based on measuring Doppler shifts in a tone that is emitted from a mobile beacon.…”

“…The Doppler effect has been used extensively to estimate the velocity of tracked objects or to improve the accuracy of tracking systems [15], [16]. In [15], the self-localization of sensors is developed based on measuring Doppler shifts in a tone that is emitted from a mobile beacon. Each static node updates its location information by using the location and heading of the beacon as well as the frequency of the acoustic tone.…”

“…Modern air traffic control radars use the Doppler effect to discriminate moving aircraft from stationary targets [38]. Even though several localization techniques based on Doppler effect have been proposed, none of these schemes target the case when nodes and beacons can move [15], [16]. Using the Doppler effect in our proposed architecture as a verification of GPS/INS is attractive since it relies on the smoothness of the Doppler shift and the ability to predict it with low, essentially constant errors over long periods of time.…”

A Survey of Time Delay Estimation Performance Bounds

“…In aeroacoustics (sounds propagating through air), signal coherence degrades with increased spatial separation between the sensors due to random scattering caused by atmospheric turbulence. Physics-based statistical models for the coherence as a function of frequency, range, weather conditions, and sensor separation are reviewed and applied to signal processing performance analyses in [50], [24], [34], [23], [25]. Scattering and coherence losses occur in underwater acoustics, e.g., see [31] for an early analysis of the CRB on TDE with scattering, with more recent work in [5], [19] and elsewhere.…”