Neuromorphic SLNN-Based Multiband Active Camouflage and Sensor Deception Metacontrol System

Modern sensing systems increasingly combine visible imaging, long-wave infrared imaging, multispectral observation, and vision-based tracking algorithms. Conventional passive camouflage and fixed-color coatings are therefore limited under changing backgrounds, seasonal variation, platform heat emission, surface contamination, and physical damage. This preprint proposes a neuromorphic metacontrol architecture for multiband active camouflage based on a Spiking Liquid Neural Network(SLNN). The proposed system treats active camouflage not as a perfect invisibility mechanism, but as a measurable sensor-deception problem: reducing background contrast, delaying identification, and degrading tracking stability.

The architecture combines a physical tile layer, consisting of visible-band reflective modulation and infrared apparent-emissivity modulation candidates, with an SLNN-based online adaptive control layer. The SLNN does not directly replace low-level safety controllers. Instead, it updates tile-level target states, correction weights, thermal spreading priorities, and damaged-tile avoidance weights above local drivers. Its recurrent hidden assembly, 3-factor spike-timing-dependent plasticity(STDP), dual neuromodulation, and conflict/plasticity state variables are mapped to background prediction, tile response drift compensation, and graceful degradation under damage or contamination. The preprint also clarifies why active camouflage is more suitable for SLNN-based control than prior phase-cancellation tasks such as active noise cancellation: the problem is dominated by pattern/amplitude matching and spatial preview rather than microsecond-level phase alignment. Evaluation metrics are proposed, including ΔE2000, apparent ΔT, latency percentiles, power density, tile recovery time, detection probability, and tracking break rate.

**Keywords:** SLNN; spiking neural network; neuromorphic control; active camouflage; multispectral sensing; sensor deception; adaptive control; 3-factor STDP; tunable emissivity; electrochromic materials