CASCADE project

4D radar with a cascaded architecture for object detection and tracking

A prototype built on TI's multi-chip AWR2243 (RF-EVM) cascade and the MMWCAS-DSP-EVM capture module. The radar "sees" through darkness, fog and smoke where optics and lidar fail — making it suitable for autonomous platforms, perimeter security and search-and-rescue missions.

Technical specifications Join the team
350 m
detection range
12 TX / 16 RX
transmitters / receivers
86
virtual MIMO channels
drag to rotate
100 m 200 m 300 m 0° 90° 180° 270° 243m
Why radar, not a camera or lidar

Microsecond-long 76–81 GHz chirps pass through rain, dust and darkness, measuring range, angle and velocity simultaneously. Cascading several AWR2243 chips enlarges the phased antenna array's aperture, so the system sees farther and resolves objects more precisely than an ordinary single-chip sensor.

Choose the radar variant
REC · Hardware rotation capture
360° RF BOARDS
AWR2243 · MMWCAS-DSP-EVM 360° view of the cascaded RF boards
Prototype hardware

Hardware platform

4 × AWR2243, 76–81 GHz

Radar module

short-range radar with high angular resolution

Boards MMWCAS-RF-EVM + MMWCAS-DSP-EVM
Transmitters / receivers 12 TX / 16 RX
Virtual MIMO array 86 channels
Processing DSP board (TDA2)

Detection range and cost

Based on TI data

Estimated detection range for different object types and the approximate cost of the prototype boards.

Detection range · FPV drone ~50–90 m
Detection range · person 150 m
Detection range · car 350+ m
Board price $4,275 + $3,844.65
How it works

From chirp to object coordinates

01

Chirp transmission

Antennas on the board form a frequency-modulated 76–81 GHz signal aimed at the object within a 120° azimuth sector.

02

Cascaded reception

Four synchronized AWR2243 chips receive the reflected signal as a single phased antenna array.

03

DSP capture

The MMWCAS-DSP-EVM reads raw ADC data and raw data from the DSP FPGA board, then performs further processing.

04

Object data output

Range, angle and velocity of objects are sent over CAN-FD, Ethernet or to the host system.

Prototype in hardware

From evaluation board to a working prototype

An FMCW Image Radar assembled into a working rig, controlling a rotating platform with two optical channels based on AI object recognition via a Hailo hardware accelerator for real-time operation.

Cascaded AWR2243 RF board, top view, cut out from background
01 · Cascaded AWR2243 RF board
Assembled MMWCAS-DSP-EVM with power indicators active, cut out from background
02 · Assembled MMWCAS-DSP-EVM
Hailo accelerator board on a HAT+ for Raspberry Pi 5, cut out from background
03 · Hailo accelerator on a Raspberry Pi 5
Dual-camera module on a servo gimbal, cut out from background
04 · Dual-camera module on a servo gimbal
Field rig with a camera on a rotating platform and tripod, cut out from background
05 · Working rig with a rotating platform
Live demonstration

Camera and radar — in sync

The first video is a synchronized capture of the camera feed and the radar's point cloud (range-azimuth) in nighttime city traffic: the radar keeps a solid lock on objects where oncoming headlights blind the camera. The second is a recording of the live 3D point-cloud viewer, showing the same data in real time and space.

REC · Live capture
02:50 RANGE-AZIMUTH
AWR2243 · MMWCAS-DSP-EVM Night footage · city traffic
REC · Viewer capture
3D VIEWER POINT CLOUD
AWR2243 · MMWCAS-DSP-EVM 3D viewer · live point cloud
Where it's used

Use cases

Autonomous ground and aerial platforms

Obstacle detection and object tracking regardless of lighting or weather.

Perimeter security & monitoring

Detecting movement along a border or security perimeter at ranges up to 350 m.

Search and rescue operations

Finding people in smoke, darkness or dense vegetation where optics fail.

Industrial & agricultural monitoring

Tracking machinery and objects across open sites and fields.

Project authors

Team

Partners

Who supports the project

Registration

Join the trials

Leave your contact details if you'd like to take part in the team's trials or help with development.

Team contacts

Want project details or a collaboration — get in touch

Team CASCADE
Faculty / department Igor Sikorsky Kyiv Polytechnic Institute, Educational and Scientific Institute of Physics and Technology
QR code linking to the team's contact email
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Software

SEES THROUGH DARKNESS. DETECTS FIRST. REACTS FASTER.

A cascaded 4D radar built on TI's AWR2243 for detecting and tracking objects through darkness, fog and smoke.

CASCADE radar software: 3D point cloud, camera feed with object detection, XY projection, and a range-doppler map