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Space-Time Adaptive Processing for radars in Connected and Automated Vehicular Platoons

Zahra Esmaeilbeig, Kumar Vijay Mishra, Mojtaba Soltanalian

TL;DR

The paper tackles interference-robust space-time adaptive processing for radar networks in connected and automated vehicle platoons by introducing a cooperative STAP framework and a time-division multiplexing transmitter scheduling scheme. The transmitter scheduling problem is cast as a quadratic assignment problem (QAP) with CPI length $L=KN$, solved via power-method-like iterations in which each step reduces to a linear assignment solvable by the Hungarian algorithm. This yields a permutation scheduling matrix $\mathbf{J}$ that maximizes the mean detector statistic $\mathds{E}\{\zeta|\mathcal{H}_1\}$, leading to improved target detection in simulations. The approach enables orthogonal, multistatic FMCW radar transmissions within CAV platoons, leveraging V2V/V2I communications for practical and scalable cooperative sensing.

Abstract

In this study, we develop a holistic framework for space-time adaptive processing (STAP) in connected and automated vehicle (CAV) radar systems. We investigate a CAV system consisting of multiple vehicles that transmit frequency-modulated continuous-waveforms (FMCW), thereby functioning as a multistatic radar. Direct application of STAP in a network of radar systems such as in a CAV may lead to excess interference. We exploit time division multiplexing (TDM) to perform transmitter scheduling over FMCW pulses to achieve high detection performance. The TDM design problem is formulated as a quadratic assignment problem which is tackled by power method-like iterations and applying the Hungarian algorithm for linear assignment in each iteration. Numerical experiments confirm that the optimized TDM is successful in enhancing the target detection performance.

Space-Time Adaptive Processing for radars in Connected and Automated Vehicular Platoons

TL;DR

The paper tackles interference-robust space-time adaptive processing for radar networks in connected and automated vehicle platoons by introducing a cooperative STAP framework and a time-division multiplexing transmitter scheduling scheme. The transmitter scheduling problem is cast as a quadratic assignment problem (QAP) with CPI length , solved via power-method-like iterations in which each step reduces to a linear assignment solvable by the Hungarian algorithm. This yields a permutation scheduling matrix that maximizes the mean detector statistic , leading to improved target detection in simulations. The approach enables orthogonal, multistatic FMCW radar transmissions within CAV platoons, leveraging V2V/V2I communications for practical and scalable cooperative sensing.

Abstract

In this study, we develop a holistic framework for space-time adaptive processing (STAP) in connected and automated vehicle (CAV) radar systems. We investigate a CAV system consisting of multiple vehicles that transmit frequency-modulated continuous-waveforms (FMCW), thereby functioning as a multistatic radar. Direct application of STAP in a network of radar systems such as in a CAV may lead to excess interference. We exploit time division multiplexing (TDM) to perform transmitter scheduling over FMCW pulses to achieve high detection performance. The TDM design problem is formulated as a quadratic assignment problem which is tackled by power method-like iterations and applying the Hungarian algorithm for linear assignment in each iteration. Numerical experiments confirm that the optimized TDM is successful in enhancing the target detection performance.
Paper Structure (6 sections, 30 equations, 2 figures, 1 algorithm)

This paper contains 6 sections, 30 equations, 2 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. TDM design
  4. solution methodology
  5. Numerical Experiments
  6. Summary

Figures (2)

  • Figure 1: A simplified illustration of a CAV platoon consisting of three vehicles, sensing a target in the FoV of all three vehicles. The radar on vehicle 1, denoted by RX/TX1, leads the platoon and is assisted by two other radars, denoted by TX2 and TX3.
  • Figure 2: RoC of detection for a CAV of FMCW radars. The optimized TDM is compared with uniform transmission where the antennas are activated uniformly in a sequence.