Indoor positioning method based on fingerprint similarity in super dense wireless network
A fingerprint similarity and wireless network technology, which is applied in the field of indoor positioning based on fingerprint similarity under ultra-dense wireless networks, can solve the problems of low positioning accuracy, instability, and huge fingerprint database
Active Publication Date: 2018-01-19
XIDIAN UNIV
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[0003] To sum up, the problems existing in the existing technology are: the existing indoor positioning method based on location fingerprints has a huge fingerprint database, and when a large number of APs in the fingerprint database are lost in an ultra-dense wireless network, the positioning accuracy is low and unstable
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[0042] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0043] The present invention reduces positioning errors and provides more robust positioning accuracy in a dynamically changing actual indoor environment. By defining fingerprint similarity to estimate the distance between different locations in an ultra-dense wireless network, a simple and efficient AP selection method is adopted. In the ultra-dense wireless network where APs are densely deployed, APs that can effectively characterize the characteristics of received signal strength in the environment are selected; a relatively stable fingerprint library is established by using the relative value of received signal strength ...
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The invention belongs to the field of wireless communication and the indoor positioning technology, and discloses an indoor positioning method based on fingerprint similarity in a super dense wirelessnetwork. The position of a target is estimated by defining flexible and stable fingerprint similarity, and the method comprises the following steps: designing a simple and efficient access point (access point, AP) selection method to select an AP that can effectively characterize the received signal intensity features in an indoor environment; and establishing a stable fingerprint database by using the received signal intensity relative values to relieve the influence of environment dynamics and isomerous receiving devices and improve the positioning precision; and a weight priority criteriondesigned online allocates a greater weight to the AP with higher signal intensity when determining the similarity of two positions so as to better resist the problem of the environment dynamics and improve the positioning precision; and particularly when a lot of APs are lost, the FSIL can provide positioning precision with better robustness.
Description
technical field [0001] The invention belongs to the technical field of wireless communication and indoor positioning, and in particular relates to an indoor positioning method based on fingerprint similarity under an ultra-dense wireless network. Background technique [0002] In recent years, the demand for location-aware applications in the Internet of Things has surged, such as positioning and guidance in actual scenarios such as hospitals, airports, and large shopping malls. At the same time, industries such as smart home, unmanned medical care, and intelligent robots also require computers to be able to identify the location of specific objects indoors, which promotes the rapid development of indoor positioning system (IPS) and brings huge prospects. At the same time, due to the rapid increase in performance of IoT devices (such as mobile phones, tablet computers, wearable devices, etc.), indoor positioning technology can bring users a better user experience. Existing i...
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IPC IPC(8): H04W4/02H04W64/00G01S11/06
Inventor 盛敏厚丹妮刘俊宇李建东张琰彭琳琳郑阳刘伟
Owner XIDIAN UNIV