Abstract: A method and related system are provided for estimating or predicting an output value of a first ambient parameter (AP). Sensors generate a plurality of time-paired training values of the first AP, a second AP, and accuracy factor(s) affecting the accuracy of the measured first or second APs. A computer uses the training values, and trust coefficients based on the accuracy factor to train an air quality prediction model for estimating or predicting the output value of the first AP based on a measured input value of the second AP. The computer estimates or predicts the output value of the first AP by applying the trained air quality prediction model to the input value of the second AP. The estimated or predicted output value of the first AP may be used to calibrate the accuracy of measured values of the first AP, or forecast future values of the first AP.

Abstract: Real-time calibration of a tunable matching network that matches the dynamic impedance of an antenna in a radio frequency receiver system. The radio frequency receiver system includes two non-linear equations that may be solved to determine the reflection coefficient of the antenna. The tunable matching network is repeatedly perturbed and the power received by the antenna is measured after each perturbation at the same node in the matching network. The measured power values are used by an optimizer in converging to a solution that provides the reflection coefficient of the antenna. The reflection coefficient of the antenna may be used to determine the input impedance of the antenna. The elements of the matching circuit are then adjusted to match the input impedance of the antenna.

Abstract: Real-time calibration of a tunable matching network that matches the dynamic impedance of an antenna in a radio frequency receiver system. The radio frequency receiver system includes two non-linear equations that may be solved to determine the reflection coefficient of the antenna. The tunable matching network is repeatedly perturbed and the power received by the antenna is measured after each perturbation at the same node in the matching network. The measured power values are used by an optimizer in converging to a solution that provides the reflection coefficient of the antenna. The reflection coefficient of the antenna may be used to determine the input impedance of the antenna. The elements of the matching circuit are then adjusted to match the input impedance of the antenna.

Abstract: Real-time calibration of a tunable matching network that matches the dynamic impedance of an antenna in a radio frequency receiver system. The radio frequency receiver system includes two non-linear equations that may be solved to determine the reflection coefficient of the antenna. The tunable matching network is repeatedly perturbed and the power received by the antenna is measured after each perturbation at the same node in the matching network. The measured power values are used by an optimizer in converging to a solution that provides the reflection coefficient of the antenna. The reflection coefficient of the antenna may be used to determine the input impedance of the antenna. The elements of the matching circuit are then adjusted to match the input impedance of the antenna.

Abstract: Real-time calibration of a tunable matching network that matches the dynamic impedance of an antenna in a radio frequency transmitter system. The radio frequency transmitter system includes two non-linear equations that may be solved to determine the reflection coefficient of the antenna. The tunable matching network is repeatedly perturbed and the power reflected by the antenna is measured after each perturbation at the same node within the tunable matching network. The power values are used by an optimizer in converging to a solution that provides input impedance of the antenna. The elements of the matching circuit are adjusted to match the input impedance of the antenna.

Abstract: Real-time calibration of a tunable matching network that matches the dynamic impedance of an antenna in a radio frequency transmitter system. The radio frequency transmitter system includes two non-linear equations that may be solved to determine the reflection coefficient of the antenna. The tunable matching network is repeatedly perturbed and the power reflected by the antenna is measured after each perturbation at the same node within the tunable matching network. The power values are used by an optimizer in converging to a solution that provides input impedance of the antenna. The elements of the matching circuit are adjusted to match the input impedance of the antenna.

Abstract: Real-time calibration of a tunable matching network that matches the dynamic impedance of an antenna in a radio frequency receiver system. The radio frequency receiver system includes two non-linear equations that may be solved to determine the reflection coefficient of the antenna. The tunable matching network is repeatedly perturbed and the power received by the antenna is measured after each perturbation at the same node in the matching network. The measured power values are used by an optimizer in converging to a solution that provides the reflection coefficient of the antenna. The reflection coefficient of the antenna may be used to determine the input impedance of the antenna. The elements of the matching circuit are then adjusted to match the input impedance of the antenna.