Ambiguity Function Shaping in FMCW Automotive Radar

TL;DR

This paper introduces a novel code optimization method for FMCW automotive radar that shapes the ambiguity function to reduce high side-lobes, thereby improving target detection in challenging scenarios.

Contribution

It presents a new framework for designing radar transmit sequences by shaping the ambiguity function, using an efficient iterative optimization algorithm for improved radar performance.

Findings

Effective suppression of ambiguity function side-lobes.

Enhanced target detection in automotive radar scenarios.

Demonstrated algorithm's superiority through numerical results.

Abstract

Frequency-modulated continuous wave (FMCW) radar with inter-chirp coding produces high side-lobes in the Doppler and range dimensions of the radar's ambiguity function. The high side-lobes may cause miss-detection due to masking between targets that are at similar range and have large received power difference, as is often the case in automotive scenarios. In this paper, we develop a novel code optimization method that attenuates the side-lobes of the radar's ambiguity function. In particular, we introduce a framework for designing radar transmit sequences by shaping the radar Ambiguity Function (AF) to a desired structure. The proposed approach suppresses the average amplitude of the AF of the transmitted signal in regions of interest by efficiently tackling a longstanding optimization problem. The optimization criterion is quartic in nature with respect to the radar transmit code. A cyclic iterative algorithm is introduced that recasts the quartic problem as a unimodular quadratic problem (UQP) which can be tackled using power-method-like iterations (PMLI). Our numerical results demonstrate the effectiveness of the proposed algorithm in designing sequences with desired AF which is of great interest to the future generations of automotive radar sensors.