Abstract: A pathogen detection method. A sample that potentially contains a pathogen is collected. A triangle wave form output is produced. A signal associated with the triangle wave form is transmitted from a voltage-controlled oscillator over a plurality of frequencies. The signal is transmitted through the sample to cause the pathogen in the sample to vibrate at a frequency. The vibrations from the sample are detected. A resonance profile of a pathogen in the sample is calculated based upon the vibrations. A database that includes a resonance profile signature of at least one pathogens is provided. The calculated resonance profile is compared to the resonance profile signature database to determine if the sample includes the pathogen.

Abstract: A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar with transceiver, a signature database, and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database, or the machine learned characteristics to determine the threat, anomaly, foreign object, material characteristics, and threat speech recognition.

Abstract: A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar, a signature database and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database or the machine learned characteristics to determine the threat, anomaly, foreign object and material characteristics.

Abstract: A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar, a signature database and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database or the machine learned characteristics to determine the threat, anomaly, foreign object and material characteristics.

Abstract: A variable operational mode transceiver device formed with an integrated circuit having a semiconductor material substrate supporting a feedback oscillator having a signal power divider electrically coupled to said feedback oscillator output, and a signal frequency multiplier electrically coupled to said signal power divider. A signal mixer has a pair of inputs of which one is electrically coupled to that remaining one of said pair of outputs of said signal power divider.

Abstract: A variable operational mode transceiver device formed with an integrated circuit having a semiconductor material substrate supporting a feedback oscillator having a signal power divider electrically coupled to said feedback oscillator output, and a signal frequency multiplier electrically coupled to said signal power divider. A signal mixer has a pair of inputs of which one is electrically coupled to that remaining one of said pair of outputs of said signal power divider.