Kalman filtering for weak signal detection in remote sensing
Remote sensing often involves probing a region of interest with a transmitted electromagnetic signal, and then analyzing the returned signal to infer characteristics of the investigated region. It is not uncommon for the measured signal to be relatively weak or for ambient noise to interfere with the sensor’s ability to isolate and measure only the desired return signal. Although there are potential hardware solutions to these obstacles, such as increasing the power in the transmit signal to strengthen the return signal, or altering the transmit frequency, or shielding the system to eliminate the interfering ambient noise, these solutions are not always viable. For example, regulatory constraints on the amount of power that may be radiated by the sensor or the trade-off between the transmit power and the battery life for a portable sensor may limit the power in the transmitted signal, and effectively shielding a system in the field from ambient electromagnetic signals is very difficult. Thus, signal processing is often utilized to improve signal detectability in situations such as these where a hardware solution is not sufficient.
