Noise is a common problem for imaging sensors. Multiframe averaging is a natural way to improve the SNR. This will inherently improve the performance of an automatic target recognizer (ATR) that has to use the imagery provided by that sensor. When the ATR is located on a weapon platform that is rapidly approaching a set of potential targets, it is appropriate to use a weighted moving average. The more recent frames are collected at ranges closer to the targets than the older frames, so they should receive more weight in the moving average. Exponential smoothing is nothing more than a weighted moving average that uses weighting factors based on the geometric progression. The advantage to using exponential smoothing is that it can be implemented in hardware for real-time applications. This paper will show that an exponentially weighted moving average is equivalent to an exponential smoothing technique. Lastly, we will describe the way in which exponential smoothing can be used in a real-time ATR to improve performance for very little cost, without a time penalty for signal processing.
Perry C. Lindberg,
"Improving SNR to improve ATR performance", Proc. SPIE 2232, Signal Processing, Sensor Fusion, and Target Recognition III, (10 June 1994); doi: 10.1117/12.177762; https://doi.org/10.1117/12.177762