Often, the lack of efficient and reliable data processing, interpretation, and quality control techniques hinders further enhancement of existing multi-signal systems as well as development and implementation of the new ones. If properly acquired, processed and interpreted, multiple signals allow significantly more efficient and reliable detection, identification, and tracking of user-specified features of the monitored medium than single signals. Examples of multi-signal systems are multiple antenna profilers for monitoring the stratosphere, multi-lead electroencephalographs for diagnosing functional pathologies in a brain, and arrays of microphones for underground sounding. The most advanced medical non-invasive diagnostic tool, the functional magnetic resonance imager, produces a temporal sequence of spatial images, and time series of signal magnitudes from multiple voxels also represent multiple received signals.

EnerLab information technologies include innovative integral and differential data processing methods, fuzzy-logic-based interpretation and decision-making algorithms, and end-to-end fuzzy-logic-based quality control algorithms for multi-signal systems.

The greatest competitive strength of our technologies is their ability to increase spatial and/or temporal resolution, mitigate artifacts like clutters and external interference in comparison with existing systems, and more. EnerLab technologies also enable to retrieve characteristics of the monitored medium which are not available with other data processing techniques. For example, one can obtain comprehensive turbulent characteristics of the atmosphere by applying advanced differential data analysis techniques to multiple antenna wind profilers.

Neither data processing methods, nor interpretation and quality control algorithms can be universal. The best solution can only be achieved by considering individual systems and their specific applications. EnerLab products are tailored to precise customer needs and our technology services may include the derivation of equations for relating parameters of multiple received signals to the customer-specified characteristics of a monitored medium, data pre-processing algorithms such as those for efficient filtering of noise and radio-electric interference components from the signals, algorithms for estimating specified characteristics of the medium as well as measurement errors and confidence for the estimates.