Statistical Signal Processing
Statistical signal processing is a field of signal processing and applied mathematics that treats signals as stochastic processes. The introduction of statistical models for the signals of interest enables the application of a variety of quality criteria as well as a large toolbox for the estimation of parameters. Depending on the statistical model for the signal of interest and underlying parameters, different estimation methods are available. For example, a parameter of a signal can be modeled as deterministic or as a random variable in order to incorporate prior knowledge. Methods of statistical signal processing are applied in various research areas in almost every scientific discipline.
Statistical signal processing is used in the following fields of research at our institute:
- Millimeter-Wave Communications
- Radar and DoA Estimation
- Multi-User MIMO Communications
- Estimation of Structured Wireless Channels
- Automotive Safety and Autonomous Driving
To learn more about statistical signal processing we kindly refer to the following lectures offered at our institute:
- Adaptive and Array Signal Processing
- Stochastische Signale
- Systeme der Signalverarbeitung
- Statistical Signal Processing
- Signal Processing and Machine Learning
- Signals and Array Signal Processing for Global Navigation Satellite Systems