Introduction and implementations of the kalman filter / / edited by Felix Govaers.
Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localiz...
Saved in:
: | |
---|---|
TeilnehmendeR: | |
Place / Publishing House: | London, England : : IntechOpen,, [2019] ©2019 |
Year of Publication: | 2019 |
Language: | English |
Physical Description: | 1 online resource (128 pages) :; illustrations |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
LEADER | 01012nam a2200301 i 4500 | ||
---|---|---|---|
001 | 993546453004498 | ||
005 | 20221015123358.0 | ||
006 | m o d | ||
007 | cr ||||||||||| | ||
008 | 221015s2019 enka o 000 0 eng d | ||
020 | |a 1-83880-739-X | ||
020 | |a 1-83880-537-0 | ||
035 | |a (CKB)4100000008408625 | ||
035 | |a (NjHacI)994100000008408625 | ||
035 | |a (oapen)https://directory.doabooks.org/handle/20.500.12854/50595 | ||
035 | |a (EXLCZ)994100000008408625 | ||
040 | |a NjHacI |b eng |e rda |c NjHacl | ||
041 | 0 | |a eng | |
050 | 4 | |a QA402.3 |b .I587 2019 | |
082 | 0 | 4 | |a 629.8312 |2 23 |
100 | 1 | |a Felix Govaers |4 auth | |
245 | 0 | 0 | |a Introduction and implementations of the kalman filter / |c edited by Felix Govaers. |
260 | |b IntechOpen |c 2019 | ||
264 | 1 | |a London, England : |b IntechOpen, |c [2019] | |
264 | 4 | |c ©2019 | |
300 | |a 1 online resource (128 pages) : |b illustrations | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
588 | |a Description based on: online resource; title from PDF information screen (InTech, viewed October 15, 2022). | ||
520 | |a Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some ""awareness"" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not. | ||
546 | |a English | ||
650 | 0 | |a Kalman filtering. | |
653 | |a Physical Sciences | ||
653 | |a Engineering and Technology | ||
653 | |a Computer and Information Science | ||
653 | |a Numerical Analysis and Scientific Computing | ||
653 | |a Signal Processing | ||
776 | |z 1-83880-536-2 | ||
700 | 1 | |a Govaers, Felix, |e editor. | |
906 | |a BOOK | ||
ADM | |b 2023-02-22 19:54:54 Europe/Vienna |f system |c marc21 |a 2019-06-21 19:11:02 Europe/Vienna |g false | ||
AVE | |i DOAB Directory of Open Access Books |P DOAB Directory of Open Access Books |x https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5351663040004498&Force_direct=true |Z 5351663040004498 |b Available |8 5351663040004498 |