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Constant Modulus Waveform Design for Slow-Time Ambiguity Function

delete2026-09-21
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OA
AI
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Weijian Zhang
S
Siqi Liu
J
Jingshan Zhao
J
Jindong Zhang *
DOI:10.3390/electronics15184320delete
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Abstract

Abstract

En 中文
This work addresses the synthesis of constant-modulus (CM) radar waveforms whose range-Doppler behavior approximates a prescribed profile in the presence of multiple interference sources. Since the interference power at the matched-filter output amounts to an average of the slow-time ambiguity function (STAF) of the transmitted code evaluated at the interference range-Doppler bins, the design task is essentially one of shaping the STAF. The resulting formulation is high-dimensional and non-convex because of the CM requirement, which hampers conventional optimization tools in Euclidean space. To circumvent this difficulty, we recast the design as an unconstrained problem on a Riemannian manifold and tackle it directly with a trust-region scheme defined on that manifold. The Riemannian gradient and Hessian of the quartic cost are derived in closed form, the trust-region subproblem is solved by a truncated conjugate gradient procedure, and the computational complexity of each iteration is analyzed. Then an enhanced solver called Adaptive regularization with cubics (ARC) is developed, improving the performance based on the step-acceptance mechanism. Numerical results under two interference scenarios show that, compared with the existing method, the proposed approach produces deeper nulls at the interference locations while requiring less computation time.
Keywords:
waveform design
ambiguity function
trust region method
Riemannian manifold

Journal

Electronics cover
Electronics
IF:
2.6
Papers:
1.1W
Citations:
4.7W

Organization

N
nanjing university of aeronautics and astronautics
Scholars:
3.7K
Papers: 1.2K
Citations: 1
Cited Papers

Cited Papers

On the Design of Constant Modulus Probing Signals for MIMO Radar
err2012-08-01
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errYong-Chao Wang; Xu Wang; Hongwei Liu; Zhi-Quan Luo
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Constant modulus sequence set design with good correlation properties
err2017-10-01
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PREAI
errCui, Guolong; Yu, Xianxiang; Piezzo, Marco; Kong, Lingjiang
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Adaptive regularization with cubics on manifolds
err2020-05-13
err0
errOAAI
errNaman Agarwal; Nicolas Boumal; Brian Bullins; Coralia Cartis
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