Kill-Probability-Maximization Guidance: Breaking from the Miss-Distance-Minimization Paradigm

Fuente: arXiv
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Autori principali: Mudrik, Liraz, Oshman, Yaakov
Natura: Preprint
Pubblicazione: 2026
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author Mudrik, Liraz
Oshman, Yaakov
author_facet Mudrik, Liraz
Oshman, Yaakov
contents Classical guidance laws aim at minimizing the miss distance, thus implicitly determining the minimum warhead lethality radius required against nominal targets. However, nonnominal targets or scenarios might render the designed warhead insufficient, causing a significant degradation in the single-shot kill probability (SSKP). We propose a guidance methodology that shifts the interceptor's objective from minimizing the miss distance to directly maximizing the SSKP, while taking into account the warhead's probabilistic lethality model. Complying with the generalized separation theorem, the new paradigm is based on modifying deterministic differential-game-based guidance laws using Bayesian decision theory. Extensive Monte Carlo simulations demonstrate consistent SSKP improvement over the standard and recently introduced estimation-aware guidance laws, when tested against nominal and nonnominal evasively maneuvering targets.
format Preprint
id arxiv_https___arxiv_org_abs_2604_17811
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Kill-Probability-Maximization Guidance: Breaking from the Miss-Distance-Minimization Paradigm
Mudrik, Liraz
Oshman, Yaakov
Systems and Control
Optimization and Control
Classical guidance laws aim at minimizing the miss distance, thus implicitly determining the minimum warhead lethality radius required against nominal targets. However, nonnominal targets or scenarios might render the designed warhead insufficient, causing a significant degradation in the single-shot kill probability (SSKP). We propose a guidance methodology that shifts the interceptor's objective from minimizing the miss distance to directly maximizing the SSKP, while taking into account the warhead's probabilistic lethality model. Complying with the generalized separation theorem, the new paradigm is based on modifying deterministic differential-game-based guidance laws using Bayesian decision theory. Extensive Monte Carlo simulations demonstrate consistent SSKP improvement over the standard and recently introduced estimation-aware guidance laws, when tested against nominal and nonnominal evasively maneuvering targets.
title Kill-Probability-Maximization Guidance: Breaking from the Miss-Distance-Minimization Paradigm
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2604.17811