scholarly journals On the Slow-Time k-Space and its Augmentation in Doppler Radar Tomography

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 513
Author(s):  
Hai-Tan Tran ◽  
Emma Heading ◽  
Brian W.-H. Ng
Keyword(s):  
Signal Processing ◽  
High Resolution ◽  
Rotational Motion ◽  
Doppler Radar ◽  
Spatial Diversity ◽  
Slow Time ◽  
Frequency Space ◽  
Target Imaging ◽  
Real Experimental Data ◽  
Radar Frequency

Doppler Radar Tomography (DRT) relies on spatial diversity from rotational motion of a target rather than spectral diversity from wide bandwidth signals. The slow-time k-space is a novel form of the spatial frequency space generated by the relative rotational motion of a target at a single radar frequency, which can be exploited for high-resolution target imaging by a narrowband radar with Doppler tomographic signal processing. This paper builds on a previously published work and demonstrates, with real experimental data, a unique and interesting characteristic of the slow-time k-space: it can be augmented and significantly enhance imaging resolution by signal processing. High resolution can reveal finer details in the image, providing more information to identify unknown targets detected by the radar.

scholarly journals Photonic RF channelizer based on 49GHz soliton crystal microcombs

2020 ◽  
Author(s):  
David Moss ◽  
Roberto Morandotti ◽  
Arnan Mitchell ◽  
xingyuan xu ◽  
mengxi tan ◽  
...  
Keyword(s):  
Signal Processing ◽  
High Resolution ◽  
Ring Resonator ◽  
Rf Receivers ◽  
High Q ◽  
Monolithically Integrated ◽  
Broadband Radio ◽  
Significant Step ◽  
Multi Wavelength ◽  
Reduced Complexity

We report a broadband radio frequency (RF) channelizer with up to 92 channels using a coherent microcomb source. A soliton crystal microcomb, generated by a 49 GHz micro-ring resonator (MRR), is used as a multi-wavelength source. Due to its ultra-low comb spacing, up to 92 wavelengths are available in the C band, yielding a broad operation bandwidth. Another high-Q MRR is employed as a passive optical periodic filter to slice the RF spectrum with a high resolution of 121.4 MHz. We experimentally achieve an instantaneous RF operation bandwidth of 8.08 GHz and verify RF channelization up to 17.55 GHz via thermal tuning. Our approach is a significant step towards the monolithically integrated photonic RF receivers with reduced complexity, size, and unprecedented performance, which is important for wide RF applications ranging from broadband analog signal processing to digital-compatible signal detection.

Adaptive Sparse Recovery of Moving Targets for Distributed MIMO Radar

2014 ◽  
Vol 933 ◽  
pp. 450-455
Author(s):  
Hui Yu ◽  
Guang Hua Lu ◽  
Hai Long Zhang
Keyword(s):  
High Resolution ◽  
Sparse Recovery ◽  
Mimo Radar ◽  
Moving Target ◽  
Recovery Algorithm ◽  
Low Snr ◽  
Computation Efficiency ◽  
Target Imaging ◽  
Moving Target Imaging ◽  
Recovery Error

The high resolution and better recovery performance with distributed MIMO radar would be significantly degraded when the target moves at an unknown velocity. In this paper, we propose an adaptive sparse recovery algorithm for moving target imaging to estimate the velocity and image jointly with high computation efficiency. With an iteration mechanism, the proposed method updates the image and estimates the velocity alternately by sequentially minimizing the norm and the recovery error. Numerical simulations are carried out to demonstrate that the proposed algorithm can retrieve high-resolution image and accurate velocity simultaneously even in low SNR.

scholarly journals Assessment of Doppler Radar Radial Wind Observation Quality from Different Echo Sources for Assimilation during the Sydney 2014 Forecast Demonstration Project

2018 ◽  
Vol 35 (8) ◽  
pp. 1605-1620 ◽  
Author(s):  
Susan Rennie ◽  
Peter Steinle ◽  
Alan Seed ◽  
Mark Curtis ◽  
Yi Xiao
Keyword(s):  
Quality Control ◽  
Control System ◽  
Statistical Analysis ◽  
High Resolution ◽  
Radial Velocity ◽  
Numerical Weather Prediction ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Demonstration Project ◽  
Prediction System

AbstractA new quality control system, primarily using a naïve Bayesian classifier, has been developed to enable the assimilation of radial velocity observations from Doppler radar. The ultimate assessment of this system is the assimilation of observations in a pseudo-operational numerical weather prediction system during the Sydney 2014 Forecast Demonstration Project. A statistical analysis of the observations assimilated during this period provides an assessment of the data quality. This will influence how observations will be assimilated in the future, and what quality control and errors are applicable. This study compares observation-minus-background statistics for radial velocities from precipitation and insect echoes. The results show that with the applied level of quality control, these echo types have comparable biases. With the latest quality control, the clear air observations of wind are apparently of similar quality to those from precipitation and are therefore suitable for use in high-resolution NWP assimilation systems.

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