limitations while improving the overall capability to eliminate false declarations of gunshots and/or ambiguous declaration locations. Even when these combined systems are employed, shots fired from far enough away will not be detected because the amount of gunshot signal (both acoustic and Infrared) eventually fades into the background signals. For acoustic systems that require the supersonic shock wave for location determination, the bullet must still be traveling at supersonic speed when it passes the sensor, and it must pass the sensor within the lateral span of the shock wave. For infrared sensing of the flash upon a weapon's discharge, the bullet path is not determined. Combining these two approaches improves the capability under various conditions anticipated in a combat scenario. Both optical and acoustic sensors have been used from vehicles while on the move in urban and rural environments. These sensors have been tested on airborne and waterborne platforms as well. Electro-optical detection systems currently tested (2011) can process the incoming shot signatures at very fast speeds, providing an excellent method not only to discriminate between weapon firings and other non-gunshot events but also to identify categories, characteristics, and sometimes specific weapon types automatically. Discriminating gunfire Many techniques can be used to discriminate gunfire (also referred to as “classifying gunfire”) from similar noises such as cars backfiring, fireworks, or the sound of a helicopter passing overhead. Analysis of the spectral content of the sound, its envelope, and other heuristics are also commonly used methods to classify whether loud, sudden sounds are gunfire. Identifying the source of the sounds can be subjective, and companies such as ShotSpotter revise their records based upon information they receive from police agencies, so that a sound originally classified by the automated system as the beat of helicopter rotors has been reported first as three, then four, and finally as the sound of five separate gunshots. As a result, this technology has been rejected in court cases as non-scientific for the purpose of legal evidence. It is meant to be an investigative tool rather than a source of primary legal evidence. Another method of classifying gunfire uses "temporal pattern recognition," as referred by its developer, that employs artificial neural networks that are trained and then listen for a sound signature in acoustic events. Like other acoustic sensing systems, they are fundamentally based on the physics of acoustics, but they analyze the physical acoustic data using a