DocumentCode
257847
Title
A novel approach to UWB millimeter high resolution range detection
Author
Sims, Robert D. ; Aloi, Daniel N. ; Jia Li
Author_Institution
Electr. & Comput. Eng., Milford, MI, USA
fYear
2014
fDate
3-5 Dec. 2014
Firstpage
689
Lastpage
693
Abstract
The Non-linear Gaussian Recursive Algorithm (NGRA) is a novel algorithm that solves some of the known short range radar impairments. These short range radar impairments include clutter, overlapping echo pulses, antenna pulse distortion, and poor distance resolution. The NGRA accurately models the source signal and subtracts it from the original signal which allows for additional peaks to be detected. In order to model the primary signal and its side lobes, a sum of Gaussian model was chosen. To estimate the models coefficients a non-linear fit algorithm is required using initial conditions generated from a peak detector. The coefficients from the model provide location information and distance resolution beyond the limitations of the sampling rate of the captured data. Through experimentation the NGRA algorithm was proven to be accurate and reliable, achieving between one to eight percent error rates.
Keywords
Gaussian processes; echo; radar clutter; ultra wideband antennas; ultra wideband radar; Gaussian model; NGRA algorithm; UWB millimeter high resolution range detection; antenna pulse distortion; clutter; distance resolution; nonlinear Gaussian recursive algorithm; overlapping echo pulses; peak detector; short range radar impairments; Brain models; Equations; Mathematical model; Radar; Signal processing algorithms; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal and Information Processing (GlobalSIP), 2014 IEEE Global Conference on
Conference_Location
Atlanta, GA
Type
conf
DOI
10.1109/GlobalSIP.2014.7032206
Filename
7032206
Link To Document