Application of compressed sensing to stretch processing in radar

• Main Author: Padmanaban Karthikeyan
• Other Authors: Justin Dauwels
• Format: Theses and Dissertations
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio
• Online Access: http://hdl.handle.net/10356/65173
• Institution: Nanyang Technological University

Stretch processing is a pulse compression technique used in Radio Detection and ranging (RADAR) devices by which we can utilize the advantage of both short pulse and long pulse. Short pulses help to achieve good range resolution and long pulse with high transmitted power helps to recover targets at long distances. Usually LFM signal is transmitted and it's reflected back again by the scatterers. The reflected signal contains the information about the targets and we need a de-chirping signal to remove the carrier and recover the information. Thus the de-chirped signal is used to provide the information about the targets which are present inside the range window. Stretch processing is mostly used in high bandwidth systems where number of samples required to process the information is quite huge. After De-chirping the signal compressed sensing (CS) algorithm is applied to approximate the sparse signal. Since the reflected signal is sparse, the essential or nonzero coefficients can be recovered by means of reduced number of measurements rather than sampling the signal in Nyquist rate. Thus the complexity is reduced and time taken to reconstruct the target profile is also reduced by which CS algorithm achieves an advantage over the conventional sampling. Compressive Sampling Matching Pursuit (CoSaMP) is a greedy iterative algorithm for approximating the sparse signal by reduced number of measurements and it's used for CS reconstruction. CoS aMP produces much stable reconstruction by including much simpler sampling matrices and the number of samples required is Jesser than other algorithms. CoSaMP algorithm is even able to accurately reconstruct the closely spaced scatterers which are contaminated by noise and CS can also be used to locate the off-grid targets.