This post will briefly summarize useful references on Statistical Signal Processing (SSP). Often, a course on Estimation and Detection Theory also covers similar topics and hence, in academia the names are most often used interchangeably.
Estimation Theory
A course on estimation theory usually covers the following topics:
- Sufficient statistics
- Minimum variance unbiased estimation
- Cramer-Rao lower bound
- Maximum likelihood and Bayesian estimation
- Wiener and Kalman filtering
Detection Theory
A course on detection theory usually covers the following topics:
- Bayesian risk theory
- Neyman-Pearson detection
- Signal detection in Gaussian noise
- Bayes factors and GLRTs
- CFAR detection
References
Web-page for this MIT OCW course was very helpful. To find the course notes accompanying the course, refer to this link and iterate through the chapters by modifying the URLs. I found these set of notes to be very comprehensive and meticulous.
This is another excellent reference with video lectures available on YouTube. This reference also covers a broad range of topics in depth.