This work investigates how multipath propagation can be exploited to enhance the accuracy of AoA localization systems. The presented multipath assisted method resembles a fingerprinting approach, matching an AoA measurement vector to a set of reference vectors. 

The IEEE Signal Processing Society Chapter of the Year Award will be presented for the eighth time in 2019. The award will be presented annually to a Chapter that has provided their membership with the highest quality of programs, activities and services. The award will be presented annually in conjunction with the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) to the Chapter’s representative.

IEEE SPS has built a streamlined mechanism for employers to add a job announcement by simply filling in a simple job opportunity submission Web form related to a particular TC field.

Please refer to the following webpage for the latest updates on upcoming conferences in Signal Processing. Listing of all conferences

he Signal Processing Society (SPS) has 12 Technical Committees and 3 Special Interest Groups (SIGs) that support a broad selection of signal processing-related activities defined by the scope of the Society. 

Will autonomous vehicles kill people? The answer is almost certainly yes. But, human drivers kill people too. In 2016 the U.S. had 37,461 deaths in 34,436 human-operated motor vehicle crashes, a staggering average of 102 per day, according to the National Highway Traffic Safety Administration. An additional 2,350,000 are injured or disabled. These figures are alarming, but there’s a solution on the horizon.

The IEEE Signal Processing Society continues to track emerging technical areas. As a result, the Society has decided to create two new SPS Technical Interest Profile (TIP) Code categories in the fields of Data Science and Autonomous Systems to keep pace with the expanding technical disciplines.

Speech coding is a field in which compression paradigms have not changed in the last 30 years. Speech signals are most commonly encoded with compression methods that have roots in linear predictive theory dating back to the early 1940s.