LEARNING CENTRE

Radar Academy

Radar physics, detection, tracking and classification as one connected learning path. Alongside the method, every module also explains its limits and how much evidence it actually contributes to radar-based drone detection.

Topics

Published by Ozense
Last reviewed: 17 August 2026

RADAR PHYSICS
01

FMCW Basics

Chirps, beat frequency and range–Doppler processing as the foundation of range and velocity measurement.
02

Radar Resolution

Range, velocity and angle resolution: understanding bandwidth, observation time and spatial aperture separately.
03

Radar Cross Section (RCS)

Scattering theory, aspect dependence and statistical fluctuation of radar backscatter.
04

Multipath Effects

Two-ray model, Fresnel zones and ghost targets in real radar environments.
MOTION & SIGNAL
05

CRT & Velocity Ambiguity

Reconstructing and robustly interpreting velocity wrapping and Doppler ambiguity from multiple modulo views.
DETECTION
06

Clutter & CFAR

Adaptive detection thresholds, clutter distributions, CFAR variants and false-alarm considerations.
TRACKING
07

Radar Tracking

From measurement candidate through tentative and confirmed tracks to coasting, reacquisition and termination.
08

Bayesian Tracking

Combining prediction, measurement and uncertainty with the Bayes filter, Kalman, PDA, IMM and track existence.
CLASSIFICATION
09

Drone or Bird? · Micro-Doppler

Physically interpreting RCS overlap, kinematics, bulk and micro-Doppler, and temporal evidence.
10

Classification with CRNN

Radar representation, CNN, temporal modelling, Unknown, domain shift and a robust evaluation design.
SYSTEM CONTEXT
11

Radar, Camera & Privacy

Data paths, data minimisation, local processing and privacy by design, without a blanket compliance claim.

Framing

These modules explain general radar methods and their limits. They are learning material, not proof of Ozense system performance. How the methods work together in the system is covered under Technology; the measured development status is under Validation.