Abstract
In this paper an algorithm is presented that recursively computes the maximum likelihood (ML) estimates of an aircraft's position in space. By combining an a priori ML estimate of the aircraft's state vector and its error covariance matrix with multiple range measurements, updated estimates are obtained. This technique is particularly useful in situations where distance measuring equipment coverage or geometry is poor and VHF OMNI range (VOR) signals are available.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.