CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Exploitable results
Statistical array signal processing deals with processing the output data of an array of antennas. The purpose is to obtain insight into the structure of waves carrying information and traversing the array.
In this project, the advanced statistical signal processing methods for sensor arrays with major applications to radar and communications have been developed and studied.
The direction finding algorithms based on modern resampling schemes (estimator banks) have been proposed. These procedures have been shown to achieve dramatically improved threshold performances relative to existing high-resolution direction finding methods and may be strongly recommended for a monitoring of non-stationary environments in radar and communications where the sample size is severely restricted by the stationarity interval. Also, structured and Toeplitz completion algorithms have been studied allowing to obtain essential benefits from the specific (uniform) geometry of a sensor array. Fats and efficient signal parameter estimation and adaptive beaforming methods have been also elaborated. In particular, robust adaptive beaforming and signal estimation algorithms for complicated environments have been designed. A wide class of adaptive beaforming algorithms have been obtained which are insensitive to interference and array rapid motion and fluctuations, and can be effectively used in randomly inhomogeneous and non-stationary environments. Following this research, several efficient signal detection and parameter estimation techniques for inhomogeneous media were proposed, and inter-source decorrelation algorithms with computationally simple adaptive implementations have been studied. The last type of algorithms makes the direction finding insensitive to multipath and mutual source correlation. For the case of a fully unknown environment, robust "blind" multiple input/multiple output methods for channel estimation and equalization have been proposed. These techniques have a strong potential application to digital wireless communication systems.
Computationally efficient two-dimensional wideband signal parameter estimation methods have been developed and optimal geometries for DOA estimation have been derived. Highly-concurrent fast DOA tracking algorithms for separating rapidly moving communication users have been formulated.
The algorithms and methods developed have been verified and compared with existing approaches using radar, communication, sonar, ultrasonic, and seismic experimental data. The results of this testing have shown improved performances of our advanced techniques as compared to traditional array processing methods.
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