Signal and Sensors Research Group

Our Research Focus

We develop novel algorithms, systems, and mathematical methodologies across the full radar and sensing pipeline — from waveform optimization and hardware prototyping to advanced statistical detectors and model-aided deep learning.

01 // Research Thrusts

Core Methodological Frameworks

Click each research thrust to expand detailed mathematical signal models, hardware specifications, and specific investigative thrusts.

Our primary research thrust develops and analyses a channel matrix-based data model for MIMO radar and sonar. Unlike conventional covariance-based approaches, this framework explicitly captures the linear time-varying channel between transmit waveforms and received signals, enabling more expressive clutter models and tighter statistical bounds. We derive GLRT detectors, study their asymptotic distributions, and compare channel matrix and covariance-based clutter representations across a range of operational scenarios.

INVESTIGATIVE WORKFLOWS & TOPICS
Channel matrix data model for MIMO radar / sonar returns
Generalised Likelihood Ratio Test (GLRT) detector derivation
Asymptotic distribution and false alarm rate analysis
Comparison of channel matrix vs. covariance-based clutter models
Waveform-dependent clutter modelling

Designing adaptive detectors and optimizing transmit waveforms for cognitive radar operating in clutter-rich environments, including SINR/MI-based waveform design and jammer-robust detection across complex spectral domains.

INVESTIGATIVE WORKFLOWS & TOPICS
Cognitive radar adaptive detection algorithms
Information-theoretic and SINR waveform optimization
Jammer-robust detection in non-Gaussian noise
Performance assessment under model misspecification
02 // Infrastructure

Lab Facilities & Testbeds

State-of-the-art radar testbeds, SDR transceiver platforms, and high-performance computing clusters powering our empirical experiments.

TESTBED 01

FMCW Radar Testbed

FMCW radar platform for indoor and outdoor experiments, supporting range-Doppler processing, vital sign monitoring, and human activity recognition campaigns.

Technical Specs
X-band / mmWave transceivers
Range-Doppler 2D/3D imaging
Real-time DSP streaming interface
TESTBED 02

Signal Processing Lab

High-performance workstations with MATLAB, Python, and GPU-accelerated deep learning frameworks for algorithm development, simulation, and dataset generation.

Technical Specs
NVIDIA RTX GPU clusters
MATLAB Phased Array & Radar Toolboxes
PyTorch / TensorFlow accelerated workflows
TESTBED 03

Software Defined Radios (SDRs)

Flexible SDR platforms enabling rapid prototyping and real-time experimentation with custom waveforms, adaptive signal processing, and over-the-air radar and communications research.

Technical Specs
USRP / LimeSDR transceivers
Wideband RF front-ends
GNU Radio & custom Python SDR pipelines
03 // Global Network

Academic & Industry Partners

Collaborating with leading global institutions and industry leaders to pioneer breakthrough sensing innovations.

academicUSA

Duke University

Joint research in theoretical radar signal processing and statistical detector derivations.

academicUSA

Arizona State University

Collaborative thrusts in channel matrix-based MIMO radar models and cognitive sensing.

industryPakistan

Electrodynamics Pvt. Ltd.

Industry-funded prototyping for Passive WiFi Radar and Ground Penetrating Radar systems.