10.6 Application of the SSKF to the DIFAR Ship Tracking Case Study
Since the dynamic equation is linear for the DIFAR tracking problem, the SSKF process used for this problem is identical to that shown in Table 9.2, except for the upper limit of the summation.
Step 1. | Filter initialization: | Set |
Initialize and | ||
Step 2. | State vectorprediction: | |
Step 3. | Observation- related prediction: | |
Get Bayesian Estimation and Tracking: A Practical Guide now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.