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
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;
Conference_Titel :
Signal and Information Processing (GlobalSIP), 2014 IEEE Global Conference on
Conference_Location :
Atlanta, GA
DOI :
10.1109/GlobalSIP.2014.7032206