On Joint Range and Velocity Estimation in Detection and Ranging Sensors
2016 (English)In: Proceedings of 19th International Conference on Information Fusion (FUSION), Institute of Electrical and Electronics Engineers (IEEE), 2016, 1674-1681 p.Conference paper (Refereed)
Radar and sonar provide information of both range and radial velocity to unknown objects. This is accomplished by emitting a signal waveform and computing the round trip time and Doppler shift. Estimation of the round trip time and Doppler shift is usually done separately without considering the couplings between these two object related quantities. The purpose of this contribution is to first model the amplitude, time shift and time scale of the returned signal in terms of the object related states range and velocity, and analyse the Cramér-Rao lower bound (CRLB) for the joint range and velocity estimation problem. One of the conclusions is that there is negative correlation between range and velocity. The maximum likelihood (ML) cost function also confirms this strong negative correlation. For target tracking applications, the use of the correct covariance matrix for the measurement vector gives a significant gain in information, compared to using the variance of range and velocity assuming independence. In other words, the knowledge of the correlation tells the tracking filter that a too large range measurement comes most likely with a too small velocity measurement, and vice versa. Experiments with sound pulses reflected in a wall indoors confirm the main conclusion of negative correlation.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. 1674-1681 p.
Cramér-Rao lower bound (CRLB), time scale, Doppler shift, time shift, time delay, tracking
Control Engineering Signal Processing
IdentifiersURN: urn:nbn:se:liu:diva-130476ISBN: 978-0-9964527-4-8OAI: oai:DiVA.org:liu-130476DiVA: diva2:951582
19th International Conference on Information Fusion, Heidelberg, Germany, July 5-8, 2016
ProjectsVirtual Photo Studio (VPS)Scalable Kalman Filters
FunderSwedish Foundation for Strategic Research , IIS11-0081Swedish Research Council