One of the more interesting and mathematically challenging applications of an array of sensors is to be able to recover just the conversation of interest, in the clear without the noise.  To make the problem even more interesting, suppose that it is unknown whether or not that weak signal is even present, but if and when it is, we want to pinpoint where it’s coming from as well as receive it clearly.  Even more generally, we may want to separate out and isolate each and every ‘emitter’ in that environment, without having any a priori information about who’s in the crowd and when they’re speaking.

Mathematically, we refer to this signal separation process as Blind Signal Sorting, or BSS, where the term ‘blind’ means that nothing is known about the signal environment. 

The problem is to decompose the signal environment into its many independent components.  With an array of sensors, each simultaneously sampling the environment from different perspectives, each sensor provides a unique and different combination of the signals, in essence providing an independent set of simultaneous equations which can be solved for the unknowns.

Our interest is primarily in electromagnetic (RF) signals.  One of the simplest yet highly effective applications is to reject, or null, deliberate jamming signals interfering with a desired communications signal.  In this case, one usually knows a great deal about the desired signal, so a general BSS operation is not necessary. 

At the other extreme, consider a surveillance application where one wants to know “what’s out there”.  Ordinarily, on the surface of the earth, transmit frequencies can be reused if the transmitters are far enough apart due to range attenuation (like cellular) or if they are beyond the (earth curvature) horizon for higher powered transmissions (like FM or TV broadcast), so ordinarily there is little co-channel interference.  If the surveillance sensor is carried above the earth’s surface, such as on an aircraft, emitters that were hidden by the earth’s curvature now are visible and interfering with one another.

An array with BSS processing can address this situation, separating the signals and providing unique phasing vectors, called “steering vectors”.  These steering vectors are applied mathematically in an input weighting and combining network to enhance a signal of interest and suppress all the others. Sometimes, a signal of interest arrives at the array indirectly, by scattering reflections which introduce severe frequency dependent distortions, often mixing in frequency dependent distorted interference.  Our frequency domain channelized BSS algorithms also address this situation