HYBRID MIMO PHASED ARRAY RADAR RECEIVE SIGNAL PROCESSING

2016 ◽  
Author(s):  
Marco La Manna
Keyword(s):  
Signal Processing ◽  
Phased Array ◽  
Receive Signal ◽  
Phased Array Radar

scholarly journals Optimal True Time Delay Filter With Application to FPGA Firmware‐Based Phased Array Radar Signal Processing

Radio Science ◽  
2019 ◽  
Vol 54 (9) ◽  
pp. 810-821
Author(s):  
Markku Lehtinen ◽  
Baylie Damtie ◽  
Mikko Orispää
Keyword(s):  
Signal Processing ◽  
Time Delay ◽  
Phased Array ◽  
Radar Signal ◽  
Radar Signal Processing ◽  
Phased Array Radar ◽  
True Time Delay ◽  
True Time

Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar

2011 ◽  
Vol 28 (12) ◽  
pp. 1581-1597 ◽  
Author(s):  
Christopher D. Curtis ◽  
Sebastián M. Torres
Keyword(s):  
Signal Processing ◽  
Phased Array ◽  
Matched Filter ◽  
Meteorological Data ◽  
Weather Radar ◽  
Meteorological Variable ◽  
Seamless Integration ◽  
Computational Burden ◽  
Phased Array Radar ◽  
Spatial Coverage

Abstract This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2 while producing meteorological data with similar quality. Adaptive range oversampling uses moment-specific transformations to minimize the variance of meteorological variable estimates. An efficient algorithm is introduced that allows for seamless integration with other signal processing functions and reduces the computational burden. Through signal processing, a new dimension is added to the traditional trade-off triangle that includes the variance of estimates, spatial coverage, and update time. That is, by trading an increase in computational complexity, data with higher temporal resolution can be collected and the variance of estimates can be improved without affecting the spatial coverage.

Hybrid-MIMO and phased array receive signal processing

2016 ◽  
Author(s):  
Marco La Manna ◽  
Daniel R. Fuhrmann
Keyword(s):  
Signal Processing ◽  
Phased Array ◽  
Receive Signal

Scalable front-end digital signal processing for a phased array radar demonstrator

2012 ◽  
Author(s):  
Felix Winterstein ◽  
Gunther Sessler ◽  
Maria Montagna ◽  
Magdalena Mendijur ◽  
Guillaume Dauron ◽  
...  
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Phased Array ◽  
Digital Signal ◽  
Front End ◽  
Phased Array Radar

Overview of the Airborne Phased Array Radar Observing Simulator

2021 ◽  
Author(s):  
Wen-Chau Lee ◽  
Jothiram Vivekanandan ◽  
Scott Ellis ◽  
Kevin Manning ◽  
George Bryan ◽  
...  
Keyword(s):  
Signal Processing ◽  
Phased Array ◽  
Software Infrastructure ◽  
High Data ◽  
Front End ◽  
Phased Array Radar ◽  
Trade Offs ◽  
Processing Software ◽  
Airborne Phased Array Radar ◽  
Specific Section

<p>The proposed airborne phased array radar (APAR) system consists of four removable, dual-polarized, C-band AESAs (Active Electronic Scanning Array) strategically located on the fuselage of the NSF/NCAR C-130. Conceptually, the radar system is divided into the front-end, the backend, and aircraft-specific section with the front-end primarily consisting of AESAs and the signal processor is in the backend. The aircraft specific section includes a power system and a GPS antenna.</p><p>As part of the risk reduction of the APAR development, the APAR Observing Simulator (AOS) system has been developed to provide simulated APAR data collection sampled from a C-130 flying by/through realistic numerical weather simulations of high-impact weather events. Given that APAR is designed to extend beyond capabilities of the existing airborne tail Doppler radars (e.g., NOAA TDRs and the retired NSF/NCAR ELDORA), a verification of signal processing software and algorithms is needed before the radar is physically built to ensure that the signal processing software infrastructure can handle high data rates and complicated, multiplex scanning that will be part of normal APAR operations.  Furthermore, several algorithms that will need to ingest large amounts of APAR data at very high rates are under development, including dual-Doppler wind synthesis, radar reflectivity attenuation correction, rain rate estimation, and hydrometeor classification. These algorithms need to be tested and verified before the implementation. </p><p>The AOS will also serve as a planning tool for future Principal Investigators (PIs) who will use it to design and test different flight and scanning strategies based on simulated storms to yield the best scientific outcomes before their field deployment takes place. This will enable better understanding of trade-offs among various sampling regimes/strategies during the planning and enhance future field programs' efficiency and effectiveness.</p>

scholarly journals Development of the Planar Active Phased Array Radar System with Real-time Adaptive Beamforming and Signal Processing

2012 ◽  
Vol 15 (6) ◽  
pp. 812-819
Author(s):  
Kwan Sung Kim ◽  
Min Joon Lee ◽  
Chang Sik Jung ◽  
Dong Jin Yeom
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Phased Array ◽  
Adaptive Beamforming ◽  
Radar System ◽  
Phased Array Radar
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