Jonathan S Abel

Title: Jonathan S. Abel: Soundfield Estimation and Seismic Data Compression

Introduction

Jonathan S. Abel is an inventor based in Menlo Park, California. His patent work addresses challenges in spatial audio and seismic data processing. He is associated with 3 patents.

Latest Patents

One patent, “Method and Apparatus for Estimating Spatial Content of Soundfield at Desired Location,” describes estimating the spatial characteristics of sound at a location where the sound may be obstructed or distorted. The approach aims to provide listeners with a more natural and spatially accurate experience, including helmet users, and may support situation-dependent processing for augmented hearing. It also describes capturing and analyzing sound from participants and devices around a field of play, then making the resulting audio components available to participants and spectators.

Another patent, “Method and System for Seismic Data Compression and Noise Reduction,” addresses the large storage and transmission demands of seismic surveys, including those using distributed acoustic sensors. The method separates collected data into signal and noise components, then compresses the estimated signal for transmission, storage, and analysis. Because the signal may have recognizable structure across traces, it can be represented with fewer parameters while preserving important information.

Career Highlights

Abel’s patents apply signal-processing concepts to two distinct technical areas. His audio invention focuses on reconstructing spatial sound for listeners, while his seismic invention seeks to reduce data burdens without discarding meaningful signal content.

Collaborations

Abel’s listed coworkers include Sean A. Coffin and Agnieszka Roginska. Their names are associated with his collaborative work in the patent and research context.

Conclusion

Jonathan S. Abel’s two patents address practical problems in spatial hearing and seismic data management, demonstrating how signal analysis can improve both sound experiences and the handling of large datasets.