Convergence properties of the multistage CMA adaptive beamformer
- 30 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 10586393,p. 622-626
- https://doi.org/10.1109/acssc.1993.342592
Abstract
The multistage CMA adaptive beamformer is capable of separating multiple narrowband sources without pilot or training signals. It is comprised of a cascade of CM (constant modulus) array subsections, each of which captures one of the signals impinging an the array. An adaptive signal canceller follows each CM array to remove captured signals from the input before processing by subsequent sections. Based an a stochastic analysis, we derive the steady-state convergence properties of the system, including its direction-finding capabilities. For mutually uncorrelated sources and noise, it is shown that the canceller exactly removes a captured signal, thereby reducing the rank of the effective array matrix of the next subsection by one.Keywords
This publication has 7 references indexed in Scilit:
- ADAPTIVE BEAMFORMERS IN COMMUNICATIONS AND DIRECTION FINDING SYSTEMSPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- The CM array: An adaptive beamformer for constant modulus signalsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Separation and bearing estimation of co-channel signalsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Maximum likelihood detection of co-channel communication signals via exploitation of spatial diversityPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Joint demodulation of cochannel signals using MLSE and MAPSD algorithmsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1993
- Signal waveform estimation in sensor array processingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1989
- A new approach to multipath correction of constant modulus signalsIEEE Transactions on Acoustics, Speech, and Signal Processing, 1983