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This paper evaluates explainability methods in safety-critical Automatic Target Recognition (ATR) systems, highlighting the limitations of post-hoc techniques like saliency and attention maps. It proposes a taxonomy and assessment framework to address issues such as spurious explanations and instability, advocating for more robust, causally grounded XAI approaches.