Finite Memory Structure Filtering and Smoothing for Target Tracking in Wireless Network Environments
In this paper, a state estimation problem is considered for a target tracking scheme in wireless network environments. Firstly, a unified algorithm of finite memory structure (FMS) filtering and smoothing is proposed for a discrete-time state-space model. As shown in the terminology <i>unified...
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| Format: | Article |
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MDPI AG
2019-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/9/14/2872 |
| _version_ | 1818421972991737856 |
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| author | Pyung Soo Kim |
| author_facet | Pyung Soo Kim |
| author_sort | Pyung Soo Kim |
| collection | DOAJ |
| description | In this paper, a state estimation problem is considered for a target tracking scheme in wireless network environments. Firstly, a unified algorithm of finite memory structure (FMS) filtering and smoothing is proposed for a discrete-time state-space model. As shown in the terminology <i>unified</i>, both FMS filter and smoother are derived by solving one optimization problem directly with incorporation of the unbiasedness constraint. Hence, the unified algorithm provides simultaneously the current state estimate as well as the lagged state estimate using only finite measurements and inputs on the most recent window. The proposed unified algorithm of FMS filtering and smoothing shows that there are some unique properties such as unbiasedness, deadbeat, time-invariance and intrinsic robustness, which cannot be obtained by the recursive infinite memory structure (IMS) filtering such as Kalman filter. The on-line computational complexity of the proposed unified algorithm is discussed. Secondly, as an application of the proposed unified algorithm, a target tracking scheme in wireless network environments is considered via computer simulations for moving target’s accelerations of various shapes. The proposed unified algorithm-based target tracking scheme provides estimates for position as well as acceleration of moving target in real time, while eliminating unwanted noise effects and maintaining desired moving positions. Due to intrinsic robustness and deadbeat properties, the proposed unified algorithm-based scheme can outperform the existing IMS filtering-based scheme when acceleration suddenly changes. |
| first_indexed | 2024-12-14T13:18:52Z |
| format | Article |
| id | doaj.art-5a708785be3e401bb96edc983d0b4125 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-14T13:18:52Z |
| publishDate | 2019-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-5a708785be3e401bb96edc983d0b41252022-12-21T22:59:58ZengMDPI AGApplied Sciences2076-34172019-07-01914287210.3390/app9142872app9142872Finite Memory Structure Filtering and Smoothing for Target Tracking in Wireless Network EnvironmentsPyung Soo Kim0Department of Electronic Engineering, Korea Polytechnic University, Siheung-si, Gyeonggi-do 15073, KoreaIn this paper, a state estimation problem is considered for a target tracking scheme in wireless network environments. Firstly, a unified algorithm of finite memory structure (FMS) filtering and smoothing is proposed for a discrete-time state-space model. As shown in the terminology <i>unified</i>, both FMS filter and smoother are derived by solving one optimization problem directly with incorporation of the unbiasedness constraint. Hence, the unified algorithm provides simultaneously the current state estimate as well as the lagged state estimate using only finite measurements and inputs on the most recent window. The proposed unified algorithm of FMS filtering and smoothing shows that there are some unique properties such as unbiasedness, deadbeat, time-invariance and intrinsic robustness, which cannot be obtained by the recursive infinite memory structure (IMS) filtering such as Kalman filter. The on-line computational complexity of the proposed unified algorithm is discussed. Secondly, as an application of the proposed unified algorithm, a target tracking scheme in wireless network environments is considered via computer simulations for moving target’s accelerations of various shapes. The proposed unified algorithm-based target tracking scheme provides estimates for position as well as acceleration of moving target in real time, while eliminating unwanted noise effects and maintaining desired moving positions. Due to intrinsic robustness and deadbeat properties, the proposed unified algorithm-based scheme can outperform the existing IMS filtering-based scheme when acceleration suddenly changes.https://www.mdpi.com/2076-3417/9/14/2872filterfinite memory structureinfinite memory structuresmoothertarget tracking |
| spellingShingle | Pyung Soo Kim Finite Memory Structure Filtering and Smoothing for Target Tracking in Wireless Network Environments Applied Sciences filter finite memory structure infinite memory structure smoother target tracking |
| title | Finite Memory Structure Filtering and Smoothing for Target Tracking in Wireless Network Environments |
| title_full | Finite Memory Structure Filtering and Smoothing for Target Tracking in Wireless Network Environments |
| title_fullStr | Finite Memory Structure Filtering and Smoothing for Target Tracking in Wireless Network Environments |
| title_full_unstemmed | Finite Memory Structure Filtering and Smoothing for Target Tracking in Wireless Network Environments |
| title_short | Finite Memory Structure Filtering and Smoothing for Target Tracking in Wireless Network Environments |
| title_sort | finite memory structure filtering and smoothing for target tracking in wireless network environments |
| topic | filter finite memory structure infinite memory structure smoother target tracking |
| url | https://www.mdpi.com/2076-3417/9/14/2872 |
| work_keys_str_mv | AT pyungsookim finitememorystructurefilteringandsmoothingfortargettrackinginwirelessnetworkenvironments |