
Enhanced direct position determination using dynamic sensor array response
Author(s) -
Eshkevari Ali,
Sadough Seyed Mohammad Sajad
Publication year - 2020
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2019.3485
Subject(s) - narrowband , algorithm , fading , computer science , position (finance) , channel (broadcasting) , attenuation , antenna array , signal (programming language) , phased array , antenna (radio) , telecommunications , physics , optics , finance , economics , programming language
An improvement in localisation of co‐channel transmitters using direct position determination (DPD) is addressed. DPD techniques estimate the locations of signal emitters by finding the peaks of a spatial pseudo‐spectral‐function (PSF) within a definite area. Actually, different algorithms/beamformers such as Bartlett, minimum variance distortionless response (MVDR), and multiple signal classification (MUSIC) are distinguished by their PSFs. Mathematically, a PSF is a function of location through the array steering/pointing vector whose elements are the channel responses between any arbitrary point in the search area and each sensor antenna for a narrowband system model. Clearly, the amplitude and phase of each complex element of the pointing vector characterise the attenuation and delay of paths between search points and sensors, respectively. Classical DPD methods do not consider the dependency of attenuation on channel path length variation during area scanning, which consequently generates PSFs full of spurious peaks. The authors propose a more realistic channel model that remarks the free‐space‐path‐loss as a deterministic, path‐length‐dependent factor beside the stochastic ones such as fading; therefore, they call it dynamic sensor array response (DSAR). Simulations show that range dependency of DSAR can effectively enhance the performance of the DPD algorithm for MVDR and MUSIC beamformers.