Optimal Parallel Waveform Design and Tracking Control of Multi-Radar Systems Using Tensor Algebra

This paper presents a new mathematical framework based on tensor algebra to enhance joint waveform guidance and control optimization (JWGCO) in multi-radar and multi-target contexts. The framework optimally minimizes a quadratic cost function related to the radar signal's energy and target tracking, accommodating pre-assigned and independently determined targets. The tensor approach translates traditional matrices into N -dimensional tensors, enabling the use of the Hadamard product for optimal control solutions linked to the tensor Riccati algebraic equation.

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Published
2025-05-03
DOI
https://doi.org/10.1109/radar52380.2025.11031984
Primary Topic
Tensor decomposition and applications
Type
article
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article

Optimal Parallel Waveform Design and Tracking Control of Multi-Radar Systems Using Tensor Algebra

Stefano Carletta, Giovanni B. Palmerini, Alfonso Farina, Francesco De Angelis
Tensor decomposition and applications
article

Optimal Parallel Waveform Design and Tracking Control of Multi-Radar Systems Using Tensor Algebra

Stefano Carletta, Giovanni B. Palmerini, Alfonso Farina, Francesco De Angelis
article en

Abstract

This paper presents a new mathematical framework based on tensor algebra to enhance joint waveform guidance and control optimization (JWGCO) in multi-radar and multi-target contexts. The framework optimally minimizes a quadratic cost function related to the radar signal's energy and target tracking, accommodating pre-assigned and independently determined targets. The tensor approach translates traditional matrices into N -dimensional tensors, enabling the use of the Hadamard product for optimal control solutions linked to the tensor Riccati algebraic equation.

Sapienza University of Rome (IT)
Affordable and clean energy
Openalex Percentile: Top 86%
Tensor decomposition and applications
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