title: Use of high sensitivity GNSS receiver Doppler measurements for indoor pedestrian dead reckoning.
abstract: Dead-reckoning (DR) algorithms, which use self-contained inertial sensors combined with gait analysis, have proven to be effective for pedestrian navigation purposes. In such DR systems, the primary error is often due to accumulated heading drifts. By tightly integrating global navigation satellite system (GNSS) Doppler measurements with DR, such accumulated heading errors can usually be accurately compensated. Under weak signal conditions, high sensitivity GNSS (HSGNSS) receivers with block processing techniques are often used, however, the Doppler quality of such receivers is relatively poor due to multipath, fading and signal attenuation. This often limits the benefits of integrating HSGNSS Doppler with DR. This paper investigates the benefits of using Doppler measurements from a novel direct vector HSGNSS receiver with pedestrian dead-reckoning (PDR) for indoor navigation. An indoor signal and multipath model is introduced which explains how conventional HSGNSS Doppler measurements are affected by indoor multipath. Velocity and Doppler estimated by using direct vector receivers are introduced and discussed. Real experimental data is processed and analyzed to assess the veracity of proposed method. It is shown when integrating HSGNSS Doppler with PDR algorithm, the proposed direct vector method are more helpful than conventional block processing method for the indoor environments considered herein.
authors.affiliation: PLAN Group, Schulich School of Engineering, The University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada. zhehe@ucalgary.ca
authors.forename: Zhe
authors.initials: Z
authors.lastname: He
authors.forename: Valérie
authors.initials: V
authors.lastname: Renaudin
authors.forename: Mark G
authors.initials: MG
authors.lastname: Petovello
authors.forename: Gérard
authors.initials: G
authors.lastname: Lachapelle
mesh_terms: D000465:Algorithms; D004301:Doppler Effect; D040362:Geographic Information Systems / Q000295:instrumentation*; D006801:Humans; D016013:Likelihood Functions; D013223:Statistics as Topic; D016138:Walking / Q000502:physiology*
references.citation: IEEE Comput Graph Appl. 2005 Nov-Dec;25(6):38-46
references.pmid: 16315476
references.citation: Sensors (Basel). 2012;12(7):8507-25
references.pmid: 23012503