A thermal decoy system contains electro-resistive fabric which warms the air within a polymer envelope transmissive to infrared radiation. The thermal decoy system thereby produces a thermal signature comparable to that of a human, which will preemptively trigger passive-infrared sensors, thereby neutralizing such sensors' capability to detect nearby persons.

A thermal decoy system contains electro-resistive fabric which warms the air within a polymer envelope transmissive to infrared radiation. The thermal decoy system thereby produces a thermal signature comparable to that of a human, which will preemptively trigger passive-infrared sensors, thereby neutralizing such sensors' capability to detect nearby persons.

A swiveling gun rest is disclosed, comprising a mounting unit for mounting to a surface of a hunting blind, and a swiveling support unit for supporting a gun and a body of a person using the gun. The mounting unit may include a mast having a foot able to contact a floor of the hunting blind. A swivel joint accommodates swivel of the support unit about a vertical axis, so as to be able to fire through windows of the hunting blind. The foot may accommodate the combined weights of the gun rest, gun, and a portion of the body weight of the person. The swivel joint may comprise a plurality of sockets fixed to the mounting unit and an equal number of fingers fixed to the support unit, the fingers configured to occupy the sockets. The support unit may comprise a frame and a cushion atop the frame.

A system, apparatus, composition and methods for producing a modular, ultra-thin, ultra-lightweight thermal camouflage, thermal signature mitigation and thermal insulation system. The thermal management system may comprise one or more composite layers or combinations of ultra-thin and ultra-lightweight non-woven stealth coated substrates. Each composite layer may be coated with specific components to create different thermal camouflage through a biomimicry application process of absorbance, reflective, protective layering, thermal signature mitigation, and/or thermal insulation system capabilities. Layers can be combined to enable dynamic stealth camouflage tunable performances of reflectivity, transmission, emissivity, or absorption in selective visible, near infrared, and infrared wavelength bands whereby each substrate has a unique EM wave propagation control or thermal signature mitigation characteristics. Embodiments enable thermal camouflage, thermal signature mitigation, and thermal insulation solutions that are adaptable to specific battlefield scenarios or environmental requirements.

A system, apparatus, composition and methods for producing a modular, ultra-thin, ultra-lightweight thermal camouflage, thermal signature mitigation and thermal insulation system. The thermal management system may comprise one or more composite layers or combinations of ultra-thin and ultra-lightweight non-woven stealth coated substrates. Each composite layer may be coated with specific components to create different thermal camouflage through a biomimicry application process of absorbance, reflective, protective layering, thermal signature mitigation, and/or thermal insulation system capabilities. Layers can be combined to enable dynamic stealth camouflage tunable performances of reflectivity, transmission, emissivity, or absorption in selective visible, near infrared, and infrared wavelength bands whereby each substrate has a unique EM wave propagation control or thermal signature mitigation characteristics. Embodiments enable thermal camouflage, thermal signature mitigation, and thermal insulation solutions that are adaptable to specific battlefield scenarios or environmental requirements.

Methods and systems fort operating one or more light sources to project adversarial patterns generated to disorient a machine learning based detection system, comprising generating one or more adversarial patterns configured to disorient the machine learning based detection system and operating one or more light sources configured to project one or more of the adversarial pattern(s) in association with the targeted object in order to disorient the machine learning based detection system.

The present disclosure provides a sub-wavelength structural material having compatibility of low detectability for infrared, laser, and microwave, which includes, from top to bottom, a metal type frequency selective surface layer I, a dielectric layer I, a metal type frequency selective surface layer II, a dielectric layer II, a resistive film, a dielectric layer III. Each of the metal type frequency selective surface layers is a sub-wavelength patch type array, and metal used by the metal type frequency selective surface layers has a characteristic of low infrared emissivity. The present disclosure modulates a phase by using a phase difference generated by patches with different sizes on the metal type frequency selective surface layer I, so as to control backscattering of incident electromagnetic waves to achieve compatibility of low detectability for laser and infrared, while the bottom three layers achieve absorption of microwave.

The present disclosure provides a sub-wavelength structural material having compatibility of low detectability for infrared, laser, and microwave, which includes, from top to bottom, a metal type frequency selective surface layer I, a dielectric layer I, a metal type frequency selective surface layer II, a dielectric layer II, a resistive film, a dielectric layer III. Each of the metal type frequency selective surface layers is a sub-wavelength patch type array, and metal used by the metal type frequency selective surface layers has a characteristic of low infrared emissivity. The present disclosure modulates a phase by using a phase difference generated by patches with different sizes on the metal type frequency selective surface layer I, so as to control backscattering of incident electromagnetic waves to achieve compatibility of low detectability for laser and infrared, while the bottom three layers achieve absorption of microwave.

A method for training a machine learning model includes obtaining camouflage material data. The method includes obtaining environmental data. The method also includes generating the machine learning model based on the camouflage material data and the environmental data. The method includes generating a plurality of camouflage patterns based on the machine learning model. The method includes assigning a rank to each of the camouflage patterns. The method further includes training the machine learning model with a camouflage pattern assigned with a highest rank.