radar-signal-processing

System-level Simulator for 5G NR-based Integrated Sensing and Communication (ISAC)

Real-time raw data acquisition, multi-dimensional signal processing, and gesture recognition for TI MIMO mmWave radar and DCA1000.

Radio-Frequency Engineering Modeling Toolkit (RF-EMT). This project provides a high-fidelity simulation framework for Radar,Telecommunication and the other Radio-frequency engineering systems. The goal is to achieve realistic, design-level system modeling and simulation.

Link-level Simulator for 5G NR-based Integrated Sensing and Communication (ISAC)

Advanced radar-based classification system for detecting and distinguishing UAVs, birds, and RC aircraft using SVMD signal decomposition and deep learning feature extraction.

Providing work samples of electromagnetic, RF, antenna, and radar system analysis that I performed for graduate school assignments.

This project implements the Time-Domain Back-Projection (TDBP) algorithm for Synthetic Aperture Radar (SAR) image reconstruction.

This repository contains simulations of various intra-pulse modulation techniques implemented in Python.

🔍 Simulate a 77 GHz FMCW MIMO radar system to estimate range, velocity, and angle of arrival for automotive applications using advanced signal processing.

Implementation of BRSR-OpGAN, a model for radar signal restoration under diverse noise and interference conditions. Includes code for data generation, training, and evaluation, with benchmarks on radar signal datasets.

Marine-radar small-target range-gate localization on the IPIX 1993 dataset — HH-polarization Vision Transformer with leakage-controlled time-block splits and a classical STDBA baseline.

Modeling and simulation of FMCW radar principles, covering waveform generation, detection, and Range-Doppler map analysis for automotive and robotics applications.

Code and experimental data for reconstructing noise-buried superoscillations and demonstrating sub-bandwidth range resolution

Radar target detection pipeline using CFAR detection and machine learning classification, built with Python

MATLAB-based MTI radar workflow for FMCW signal simulation, matched filtering, Doppler FFT, Range-Doppler mapping, and CFAR detection.

A controlled software-only evaluation of accuracy, calibration, and selective prediction for lightweight <5M parameters mmWave human-pose estimation under physics-grounded signal degradation.

Decode mmWave radar and synchronized multi-sensor sessions or live streams into Python training and real-time inference pipelines backed by Rust.