Sub-Nyquist Archives

Sub-Nyquist Sampling – DSP block

The DSP block is a system built for reconstructing the signal. The device is distributed to three data paths - the pseudo inverse of the frame matrix, the multiplication with the samples (real time reconstruction) and the support change detector. This is a customized unit for the Sub Nyquist sampling system which starts with the Wideband Analog Converter".

Tags: expand | Gidel | Nyquist | Sub-Nyquist

Sub Nyquist Sampling – Algorithm Optimization

The project is part of the Sub-Nyquist projects group. This project consists of two parts: a) A suggestion for an optimized implementation of the original system - compressing the system onto 2 FPGAs instead of 3 b) A VHDL & MATLAB simulation of the whole system

Tags: altera | Gidel | Nyquist | Sub-Nyquist

Sub-Nyquist Sampling – A/D module

The project’s goal is to integrate a sub-system that would convert the incoming analog samples to digital signals. Then they will be processed and reconstructed in the sub-Nyquist Sampling system.

Sub Nyquist Sampling – System Architecture

The goal of this project is to design a digital architecture for the Sub Nyquist algorithm implementation according to given spec and also to implement debug environment for each of its components so they could be integrated to the total architecture system

Sub-Nyquist Sampling – CTF

Multiband Reconstruction Hardware on FPGA. Implementation in hardware of the CTF - Support Recovery module.

Sub-Nyquist Sampling – Expand Sequences

The first block of the digital part of the Sub-Nyquist project. Takes 4 channels from the A2D which are sampled at high frequency (60[MHz]) and outputs 12 channels to the rest of the blocks at a lower sampling frequency (20[MHz]). The main purpose of this digital block is to use less analog hardware and to minimize costs.

Tags: expand | Gidel | Nyquist | Sub-Nyquist

Sub-Nyquist Sampling Algorithm Implementation on Flex Rio

The project is part of the Sub-Nyquist sampling and reconstruction card. Our goal was to implement DSP unit on FlexRio FPGA card under NI LabView environment, it includes integration to the full system (NI Chassis with 3 FlexRio FPGA cards).

Sub-Nyquist Sampling – Reconstruction

The project is part of the Sub-Nyquist Xampling project and a sub-module of the Reconstruction block. This project takes the frequency slices and detects the transmission bands in them highlighting the beginning and end of each band. It then filters the noises around these bands in order to get a clearer picture.

New Technics in Radar Reconstruction

For decades, radar sampling was constrained to the Nyquist theorem. Recently, new research has provided techniques to sample short-time pulses in sub-Nyquist rates, and to reconstruct them in efficient robust ways. Our project studies the existing techniques and further improves them to achieve both noise robustness and estimation accuracy.

Tags: ni | Nyquist | radar | Sub-Nyquist

Sub-Nyquist Ultrasound

Ultrasound imaging requires large amount of data to be collected and processed. New studies try to reduce the amount of data by using Sub-Nyquist techniques. The project continues this work and suggest a new digital processing method which greatly improves image quality and computation complexity.

Tags: beamfoeming | MATLAB | Sub-Nyquist | ultarsound | xampling

Multi Pass receiver

The goal of this project is to build a simulation environment for the system and to compare different compressed sensing strategies within this setting.

Tags: compressed sensing | Sub-Nyquist | UWB

Sequences investigation for the MWC

Finding optimal Mixing sequences for effective signal reconstruction. Finding the characteristics of those sequences

Tags: expander | mwc | Nyquist | Sub-Nyquist

Expander implementation using filter banks

Tags: expander | mwc | Nyquist | Sub-Nyquist

Detection of signals sampled in low rate

Implementation of the Cyclostationary feature detection Algorithm.

Tags: cyclo | Nyquist | Sub-Nyquist

Sub-Nyquist Doppler Radar System

The project consists of two main goals: 1)Low SNR Performance - By improving Doppler frequency and using knowledge from different speed bins we are able to better differentiate between targets and improve low SNR performance 2) Model Order Estimation - We compare 3 different methods of establishing a scenarios noise floor using false detection and hit/miss benchmarks

Tags: doppler | radar | Sub-Nyquist