Low-Complexity Portable Passive Drone Surveillance via SDR-Based Signal Processing

2018 ◽  
Vol 56 (4) ◽  
pp. 112-118 ◽  
Author(s):  
Hua Fu ◽  
Samith Abeywickrama ◽  
Lihao Zhang ◽  
Chau Yuen
Keyword(s):  
Signal Processing ◽  
Low Complexity

Low-Complexity Neural Networks for Baseband Signal Processing

2020 ◽  
Author(s):  
Guillaume Larue ◽  
Mona Dhiflaoui ◽  
Louis-Adrien Dufrene ◽  
Quentin Lampin ◽  
Paul Chollet ◽  
...  
Keyword(s):  
Neural Networks ◽  
Signal Processing ◽  
Low Complexity ◽  
Baseband Signal ◽  
Baseband Signal Processing

scholarly journals Photonic RF and microwave channelizer based on a Kerr soliton crystal micro-comb

2020 ◽  
Author(s):  
David Moss
Keyword(s):  
Signal Processing ◽  
Signal Detection ◽  
High Performance ◽  
Ring Resonator ◽  
Low Complexity ◽  
Analog Signal ◽  
Major Advance ◽  
Fully Integrated ◽  
High Q ◽  
Temperature Tuning

We report a 92 channel RF channelizer based on a 48.9 GHz integrated micro-comb that operates via soliton crystals, together with a passive high-Q ring resonator that acts as a periodic filter with an optical 3dB bandwidth of 121.4 MHz. We obtain an instant RF bandwidth of 8.08 GHz and 17.55 GHz achieved through temperature tuning. These results represent a major advance to achieving fully integrated photonic RF spectrum channelizers with reduced low complexity, size, and high performance for digital-compatible signal detection and broadband analog signal processing.

scholarly journals R–DFT-based Parameter Estimation for WiGig

2017 ◽  
Vol 61 (2) ◽  
pp. 224
Author(s):  
Barna Csuka ◽  
Zsolt Kollár
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Parameter Estimation ◽  
Fast Fourier Transform ◽  
Discrete Fourier Transform ◽  
Low Complexity ◽  
Estimation Methods ◽  
Ieee 802.11Ad ◽  
Parameter Estimation Methods ◽  
Processing Architecture

In this paper we present parameter estimation methods for IEEE 802.11ad transmission to estimate the frequency offset value and channel impulse response. Furthermore a less known low complexity signal processing architecture – the Recursive Discrete Fourier Transform (R-DFT) – is applied which may improve the estimation results. The paper also discusses the R-DFT and its advantages compared to the conventional Fast Fourier Transform.

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