| LAP Lambert Academic Publishing

86,950원  | 20181206  | 9786138238058

We have seen a huge increase in the use and application of a tiny device called a sensor in a number of fields. A single network may consist of many tiny sensors that sense different or same types of data. All the data sensed may vary due to data inaccuracy, inconsistency, incorrectness and imperfect so a method should be developed to get the most accurate and correct result. Data fusion is the approach by which we can get the near correct results.

Arulampalam, Sanjeev, Gordon, Neil  | Artech House

264,730원  | 20040131  | 9781580536318

For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. To solve problems beyond this restricted class, particle filters are proving to be dependable methods for stochastic dynamic estimation. This cutting-edge book introduces the latest advances in particle filter theory, discusses their relevance to defense surveillance systems, and examines defense-related applications of particle filters to nonlinear and non-Gaussian problems.