Adaptive noise cancelling is a signal processing technique that is highly effective in suppressing additive interference or noise corrupting a received target signal at the main or primary sensor in certain common situations where the interference is known and is accessible but unavoidable and where the target signal and the interference are unrelated (i.e., uncorrelated). Examples of such situations include:
Conventional signal processing techniques pass the received signal, consisting of the target signal and the corrupting interference, through a filter that is designed to minimise the effect of the interference. The objective of optimal filtering is to maximise the signal-to-noise ratio at the receiver output or to produce the optimal estimate of the target signal in the presence of interference (Wiener filter).
In contrast, adaptive noise cancelling relies on a second sensor, usually located near the source of the known interference, to obtain a relatively pure version of the interference, free from the target signal and other interference. This second version of the interference and the sensor receiving it are called the reference.
The adaptive noise canceller consists of a self-adjusting adaptive filter which automatically transforms the reference signal into an optimal estimate of the interference corrupting the target signal before subtracting it from the received signal thereby cancelling (or minimising) the effect of the interference at the noise canceller output. The adaptive filter adjusts itself continuously and automatically to minimise the residual interference affecting the target signal at its output. The power of the adaptive noise cancelling concept is that it requires no detailed a priori knowledge of the target signal or the interference. The adaptive algorithm that optimises the filter relies only on ongoing sampling of the reference input and the noise canceller output.
Adaptive noise cancelling can be effective even when the target signal and the interference are similar in nature and the interference is considerably stronger than the target signal. The key requirement is that the target signal and the interference are unrelated, that is uncorrelated. Meeting this requirement is normally not an issue in situations where adaptive noise cancelling is used.
The adaptive noise cancelling approach and the proof of the concept, the first striking demonstrations that general broadband interference can be eliminated from a target signal in practical situations using adaptive noise cancelling, were set out and demonstrated during 1971–72 at the Adaptive Systems Laboratory at the Stanford School of Electrical Engineering by Professor Bernard Widrow and John Kaunitz, an Australian doctoral student, and documented in the latter's PhD dissertation Adaptive Filtering of Broadband signals as Applied to Noise Cancelling (1972) (also available here). The work was also published as a Stanford Electronics Labs report by Kaunitz and Widrow, Noise Cancelling Filter Study (1973). The initial proof of concept demonstrations of the noise cancelling concept (see below) for eliminating broadband interference were carried out by means of a prototype hybrid adaptive signal processor designed and built by Kaunitz and described in a Stanford Electronics Labs report General Purpose Hybrid Adaptive Signal Processor (1971).