# Velocity and Angle Tracking of Fast Targets Using a Bandwidth-Coded Hybrid Chirp FMCW Radar

## TL;DR

A new radar technique uses a hybrid chirp waveform and advanced filtering to track fast-moving targets more efficiently and accurately than traditional methods.

## Contribution

A hybrid FMCW chirp waveform with bandwidth coding and unscented Kalman filtering for improved fast-target tracking.

## Key findings

- The hybrid chirp waveform enables accurate velocity estimation with only two chirps and improves maximum unambiguous velocity.
- Unscented Kalman filtering outperforms extended Kalman filtering in tracking high-speed targets under nonlinear conditions.
- The proposed method reduces IF bandwidth and ADC sampling rate compared to conventional 2D-FFT-based FMCW radar.

## Abstract

What are the main findings?
A hybrid FMCW chirp waveform with bandwidth coding enables accurate velocity estimation using only two chirps while improving the maximum unambiguous velocity limitation.Unscented Kalman filtering provides more robust and faster convergence than extended Kalman filtering for tracking high-speed targets under nonlinear measurement conditions.

A hybrid FMCW chirp waveform with bandwidth coding enables accurate velocity estimation using only two chirps while improving the maximum unambiguous velocity limitation.

Unscented Kalman filtering provides more robust and faster convergence than extended Kalman filtering for tracking high-speed targets under nonlinear measurement conditions.

What are the implications of the main findings?
The proposed approach significantly reduces the IF bandwidth and required ADC sampling rate in fast-target scenarios compared to conventional 2D-FFT-based FMCW radar methods.The framework is well suited for radar systems requiring reliable tracking of fast-moving targets at short and medium ranges, particularly in single-target applications.

The proposed approach significantly reduces the IF bandwidth and required ADC sampling rate in fast-target scenarios compared to conventional 2D-FFT-based FMCW radar methods.

The framework is well suited for radar systems requiring reliable tracking of fast-moving targets at short and medium ranges, particularly in single-target applications.

Frequency-modulated continuous-wave (FMCW) radars are widely used for range and velocity estimation. However, conventional velocity measurement techniques based on 2D-FFT processing require a large number of chirps and suffer from a maximum unambiguous velocity limitation, which restricts their applicability to high-speed targets. This study addresses these challenges by proposing a hybrid FMCW chirp waveform that employs bandwidth variation between consecutive chirps while maintaining a constant chirp duration. The proposed method enables separation of range- and Doppler-dependent frequency components using only two chirps; thus, it improves the maximum velocity constraint by keeping intermediate-frequency bandwidth and sampling requirements low. In addition, spatial angle estimation is performed using an amplitude-comparison monopulse antenna configuration, allowing single-snapshot angle measurement with low computational complexity. To enhance measurement robustness, extended and unscented Kalman filters are integrated for target tracking. Simulation results demonstrate that the proposed waveform achieves accurate velocity estimation for very high-speed targets and that the unscented Kalman filter consistently outperforms the extended Kalman filter in terms of convergence speed and robustness, particularly under poor initialization and strong nonlinearities. The results confirm that the proposed framework provides an efficient solution for tracking a single, fast-moving, isolated target in a homogeneous environment using FMCW radar systems at short and medium ranges.