BEST OF SAGEEP: Impacts of Latency on Temsense One-pass Classification Results

Summary Latency corrections are key to producing accurate inversion results from AGC data. Visual inspection of response peaks in IVS data may not be sufficient, despite passing metrics. Several QC seed failures identified within initial data reviews led to an investigation in which the impact of minute adjustments in Temsense instrument latency on classification efficacy was evaluated. Using Temsense data from multiple dynamic IVS datasets with RTK and SLAM positioning, we applied latency corrections in 0.01 second increments over a 1.2 second window. Results were inverted and classified to find the match metric, fit coherence and source offset. Plotting against the latency allowed selecting the optimal latency for the project. Results of the latency analysis were applied to one-pass datasets where QC seed failures were encountered, and classification results were assessed using optimized latency values. Improved match metric and fit coherence were observed within the data leading to passing classification results.