Postgraduate Diploma in Advanced Radar: Micro-Doppler, MIMO and Tracking
Online Postgraduate Diploma of 800 hours in Advanced Radar: Micro-Doppler, MIMO and Tracking. 8 modules covering ETSI EN 302 264, UN Regulation No. 152 and MATLAB Radar Toolbox. Dedicated tutor and open enrolment.
Postgraduate Diploma in Advanced Radar: Micro-Doppler, MIMO and Tracking — studying from Singapore
Singapore is a leading testbed for autonomous vehicles, with public road trials of driverless shuttles and robotaxis in districts such as one-north and Punggol. The Land Transport Authority coordinates the regulatory framework for autonomous mobility, while the Centre for Advanced Robotics at Nanyang Technological University and the Singapore Autonomous Vehicle initiatives drive research. Engineers work on perception, sensor fusion, vehicle software and simulation. Employers include automotive tier-one suppliers, technology firms and research institutes active across the region.
Fees for Singapore: S$1,840 (Singapore dollar), with instalments and employer sponsorship available.
Relevant bodies in Singapore
Typical roles
Questions from Singapore
Which Singapore authorities govern autonomous vehicle testing, and does SEIUM's qualification help with that?
Singapore's autonomous vehicle trials are regulated by the Land Transport Authority (LTA), which issues approvals for testing on public roads. Engineers may also register with the Professional Engineers Board (PEB). SEIUM's qualifications are private qualifications, not state degrees, and not accredited by any national body. Whether they are recognised for these roles is for employers and the relevant authorities to decide.
Which Singapore employers hire for ADAS and software-defined vehicle work?
Opportunities exist with autonomous vehicle trial operators, mobility companies, automotive electronics suppliers, and software and systems firms serving the vehicle industry. Singapore's smart mobility push supports these roles. Employers generally value demonstrable software skills, such as projects in embedded code, simulation or safety validation. Your final project can show this, but hiring decisions rest with each employer.
Is this workable part-time from Singapore, and can it be funded by an employer?
Yes, the programme is 100% online and taught in English, so you can study from home in Singapore without any student visa. Expect a heavy load: a master's is 1,900 hours, a postgraduate diploma 800 hours and a specialist course 300 hours. Fees are payable in instalments, and employer sponsorship is possible, though approval depends on your company's training policy.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Understand how automotive FMCW radars work.
Apply MIMO techniques for angle estimation.
Analyse micro-Doppler signatures to classify targets.
Process radar point clouds using modern techniques.
Implement multi-object tracking algorithms.
Integrate radar into ADAS functions and sensor fusion.
Validate radar sensors in compliance with spectral and safety regulations.
Who it's for
- Radar engineer looking to specialise in Advanced Radar: Micro-Doppler, MIMO and Tracking.
- Signal processing engineer looking to specialise in Advanced Radar: Micro-Doppler, MIMO and Tracking.
- Perception engineer looking to specialise in Advanced Radar: Micro-Doppler, MIMO and Tracking.
- Sensor fusion engineer looking to specialise in Advanced Radar: Micro-Doppler, MIMO and Tracking.
- ADAS validation engineer looking to specialise in Advanced Radar: Micro-Doppler, MIMO and Tracking.
- Radio-frequency researcher looking to specialise in Advanced Radar: Micro-Doppler, MIMO and Tracking.
- Graduates in engineering or sciences seeking to enter the automotive sector.
What you'll work with
- ETSI EN 302 264
- UN Regulation No. 152
- ISO 26262:2018
- ETSI EN 301 091
- ISO 21448:2022 (SOTIF)
- UN Regulation No. 10
- Decision 2004/545/EC
8 modules · 800 h
1.1Radar equation and radar cross-section1.2FMCW modulation and chirp ramps1.3Range and velocity resolution1.477 and 79 GHz bands1.5RF front-end architecture1.6Range-Doppler processing with FFT1.7CFAR detection1.8Doppler ambiguities and aliasing1.9Printed antennas and radomes1.10Laboratory: data cube of an FMCW radar
2.1MIMO virtual arrays2.2TDM, DDM and BPM multiplexing2.3Direction-of-arrival estimation2.4MUSIC and ESPRIT algorithms2.54D radar with elevation2.6Array calibration2.7Angular resolution and sidelobes2.8Cascaded multi-chip radar2.9Digital beamforming and Capon beamforming2.10Practical: DOA estimation with MATLAB
3.1Origin of the micro-Doppler signature3.2Short-time Fourier transform3.3Time-frequency distributions3.4Pedestrian and cyclist signatures3.5Wheel rotation and moving parts3.6Feature extraction3.7Classification with convolutional networks3.8Micro-Doppler datasets3.9Vital-sign detection with radar3.10Laboratory: pedestrian and cyclist classification
4.1Detection generation and attributes4.2DBSCAN clustering of detections4.3Ego-velocity estimation4.4Multipath and ghost suppression4.5Network-based detection on radar points4.6Occupancy grids with radar4.7Direct processing of the data cube4.8Radar-to-radar interference4.9Temporal accumulation of detections4.10Practical: segmentation of detections in RadarScenes
5.1Kalman filter and motion models5.2EKF and UKF for radar measurements5.3Data association: GNN and JPDA5.4Track management: initiation and deletion5.5Multiple-hypothesis tracking (MHT)5.6PHD and PMBM filters5.7Tracking of extended objects5.8GOSPA and OSPA metrics5.9IMM manoeuvre models5.10Laboratory: multi-object tracker in Python
6.1Object-level radar-camera fusion6.2Adaptive cruise control6.3Autonomous emergency braking6.4Blind-spot detection6.5In-cabin radar for occupant detection6.6UN Regulation No. 152 requirements6.7Euro NCAP protocols6.8Radar limitations in urban environments6.9Rear cross-traffic alert6.10Case study: analysis of an AEB case
7.1ETSI radio spectrum regulations7.2Electromagnetic compatibility7.3Radar simulation with ray tracing7.4Radar target simulators7.5Test-track validation7.6Mitigation of mutual interference7.7Functional safety of the radar sensor7.8Performance documentation7.9Anechoic chamber testing7.10Workshop: validation plan for a 4D radar
8.1Use-case specification8.2Waveform design8.3Processing and angle estimation8.4Micro-Doppler module8.5Multi-object tracker8.6Evaluation with real data8.7Analysis of limitations and improvements8.8Technical documentation8.9Report and presentation8.10Final review with the tutor
How you'll learn
Training 100% online on the SEIUM campus, with downloadable materials, recorded lectures and a dedicated technical tutor. No fixed timetable: students progress at their own pace within the intake, which makes it possible to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software includes MATLAB Radar Toolbox, Python (NumPy, SciPy), Texas Instruments mmWave Studio, Ansys HFSS, PyTorch, in free, academic or evaluation versions. Practical work covers real raw-data processing procedures for an FMCW radar, micro-Doppler classification of vulnerable road users, and evaluation of a multi-object tracker using GOSPA metrics. Assessment is continuous across modules, plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Understand how automotive FMCW radars work.
Apply MIMO techniques for angle estimation.
Analyse micro-Doppler signatures to classify targets.
Process radar point clouds using modern techniques.
Implement multi-object tracking algorithms.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical standards documentation.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme comprises 800 hours in total, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
You will work with MATLAB Radar Toolbox, Python (NumPy, SciPy), Texas Instruments mmWave Studio, Ansys HFSS and PyTorch. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An in-house SEIUM diploma upon passing the continuous assessment and the integrative project. This is not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the advanced programme. Check the credit transfer policy when enrolling.
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