Moving target motion estimation and focusing in SAR images

Author(s):  
T. Sparr
Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1478
Author(s):  
Chong Song ◽  
Bingnan Wang ◽  
Maosheng Xiang ◽  
Wei Li

A generalized likelihood ratio test (GLRT) with the constant false alarm rate (CFAR) property was recently developed for adaptive detection of moving targets in focusing synthetic aperture radar (SAR) images. However, in the multichannel SAR-ground moving-target indication (SAR-GMTI) system, image defocus is inevitable, which will remarkably degrade the performance of the GLRT detector, especially for the lower radar cross-section (RCS) and slower radial velocity moving targets. To address this issue, based on the generalized steering vector (GSV), an extended GLRT detector is proposed and its performance is evaluated by the optimum likelihood ratio test (LRT) in the Neyman-Pearson (NP) criterion. The joint data vector formulated by the current cell and its adjacent cells is used to obtain the GSV, and then the extended GLRT is derived, which coherently integrates signal and accomplishes moving-target detection and parameter estimation. Theoretical analysis and simulated SAR data demonstrate the effectiveness and robustness of the proposed detector in the defocusing SAR images.


2020 ◽  
Author(s):  
Samuele Contemori ◽  
Gerald E. Loeb ◽  
Brian D. Corneil ◽  
Guy Wallis ◽  
Timothy J. Carroll

ABSTRACTVolitional visuomotor responses in humans are generally thought to manifest 100ms or more after stimulus onset. Under appropriate conditions, however, much faster target-directed responses can be produced at upper limb and neck muscles. These “express” responses have been termed stimulus-locked responses (SLRs) and are proposed to be modulated by visuomotor transformations performed subcortically via the superior colliculus. Unfortunately, for those interested in studying SLRs, these responses have proven difficult to detect consistently across individuals. The recent report of an effective paradigm for generating SLRs in 100% of participants appears to change this. The task required the interception of a moving target that emerged from behind a barrier at a time consistent with the target velocity. Here we aimed to reproduce the efficacy of this paradigm for eliciting SLRs and to test the hypothesis that its effectiveness derives from the predictability of target onset time as opposed to target motion per se. In one experiment, we recorded surface EMG from shoulder muscles as participants made reaches to intercept temporally predictable or unpredictable targets. Consistent with our hypothesis, predictably timed targets produced more frequent and stronger SLRs than unpredictably timed targets. In a second experiment, we compared different temporally predictable stimuli and observed that transiently presented targets produced larger and earlier SLRs than sustained moving targets. Our results suggest that target motion is not critical for facilitating the expression of an SLR and that timing predictability does not rely on extrapolation of a physically plausible motion trajectory. These findings provide support for a mechanism whereby an internal timer, probably located in cerebral cortex, primes the processing of both visual input and motor output within the superior colliculus to produce SLRs.


2016 ◽  
Vol 10 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Debora Pastina ◽  
Micaela Contu ◽  
Pierfrancesco Lombardo ◽  
Marina Gashinova ◽  
Alessandro De Luca ◽  
...  

2015 ◽  
Vol 9 (1) ◽  
pp. 357-366 ◽  
Author(s):  
J. Lehtiranta ◽  
S. Siiriä ◽  
J. Karvonen

Abstract. Pairs of consecutive C-band synthetic-aperture radar (SAR) images are routinely used for sea ice motion estimation. The L-band radar has a fundamentally different character, as its longer wavelength penetrates deeper into sea ice. L-band SAR provides information on the seasonal sea ice inner structure in addition to the surface roughness that dominates C-band images. This is especially useful in the Baltic Sea, which lacks multiyear ice and icebergs, known to be confusing targets for L-band sea ice classification. In this work, L-band SAR images are investigated for sea ice motion estimation using the well-established maximal cross-correlation (MCC) approach. This work provides the first comparison of L-band and C-band SAR images for the purpose of motion estimation. The cross-correlation calculations are hardware accelerated using new OpenCL-based source code, which is made available through the author's web site. It is found that L-band images are preferable for motion estimation over C-band images. It is also shown that motion estimation is possible between a C-band and an L-band image using the maximal cross-correlation technique.


2016 ◽  
Vol 54 (1) ◽  
pp. 533-543 ◽  
Author(s):  
Gaohuan Lv ◽  
Yuan Li ◽  
Gang Wang ◽  
Yuling Zhang

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