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Multibaseline phase unwrapping (PU) is a critical processing procedure of multibaseline synthetic aperture radar interferometry (InSAR). The presence of phase noise makes Chinese remainder theorem (CRT) method not robust enough and inapplicable in practical cases. In this letter, a method based on a closed-form robust Chinese remainder theorem (CFRCRT) is presented to improve the noise robustness...
As is well known, multibaseline phase unwrapping (PU) is put forward to overcome single-baseline PU in discontinuous-terrain-height estimation. This letter presents a refined algorithm based on the cluster analysis (CA)-based noise-robust efficient multibaseline PU algorithm proposed by H. Yu. The basic idea is to combine multiple interferometric synthetic aperture radar interferograms with different...
Obstacle sensing is one of the most difficult problems in perception for unmanned ground vehicle (UGV) in outdoor environments. The regular obstacle sensors, such as stereo vision, infrared detectors and ladar, have their limited performance in unconstructed environments. In this paper, we used an ultra wideband synthetic aperture radar (SAR) to sense obstacle for UGV. The dechirp method was applied...
In traditional ground-based inierferometric synthetic aperture radar (GB-InSAR) signal processing procedure, the image registration and phase unwrapping are the necessary steps to terrain mapping. In this paper, a simplified signal processing procedure for the downward-looking GB-InSAR to terrain mapping is proposed, which focuses pairs of complex radar images on the ground-range plane by the back-projection...
Radar sensors have received more and more interest for unmanned ground vehicle to sense positive and negative obstacles in unstructured environments or out fields, especially on negative obstacle. In this paper, we present an approach for extracting the features of obstacles from radar images. Based on interferometric synthetic aperture radar (InSAR) images focused by the back-projection (BP) algorithm,...
Off-road positive and negative obstacle detection is a challenge problem to be solved by unmanned ground vehicle. Traditional sensors, such as: optical camera, lidar and millimeter wave radar, have limited performance in off-road environments, especially when obstacles are far away or covered by sparse grasses. We have proposed a forward-looking InSAR sensor to tackle the problem and have built a...
Radar sensors have received more and more interest for Unmanned Ground Vehicle (UGV) to sense positive and negative obstacles in unstructured environments or out fields. We have proposed a forward-looking InSAR can provide more information of harsh off-road environments than existing UGV based radars. The forward-looking InSAR can provide a scattering image, a coherence image and a digital terrain...
Unconstructed environments perception is a challenge problem for Unmanned Ground Vehicle (UGV) and is not well solved by traditional sensors, such as: optical camera, lidar and millimeter wave radar. This paper presents a novel forward looking InSAR (Interferometric Synthetic Aperture Radar) sensor for UGVs and focuses on reconstruction the Digital Terrain Model (DTM) of unconstructed environments...
It is a difficult task for an unmanned ground vehicle using regular sensor to sense obstacles in unstructured environments or out fields, especially on negative obstacle sensing. In this paper, we present an approach for negative obstacle sensing, based on ultra-wideband synthetic aperture radar (SAR) image characteristic of negative obstacle sensing. And real data on negative obstacle sensing is...
Forward looking InSAR can provide the heights, 2D images and coherent maps of targets ahead an unmanned ground vehicle (UGV). It is a novel alternate for an UGV to sense obstacles in unconstructed environments other than stereo cameras and LIDARs. The height is a vital feature to boost the performance of radar in obstacle discrimination. We have developed a rail based InSAR to reconstruct the 3D map...
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