A Method of Arrival Time Estimation Based on Energy Mean Detection

A technology of time-of-arrival estimation and energy mean value, applied in the field of wireless positioning, can solve problems such as high-precision positioning difficulty, and achieve the effect of good performance

Active Publication Date: 2020-05-19
SHANGHAI INTERNET OF THINGS
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  • Description
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  • Application Information

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Problems solved by technology

In summary, the existing TOA estimation methods have different performance differences at different SNRs. No algorithm can achieve better performance in all SNR ranges. There is still a certain amount of time to achieve high-precision positioning. difficulty

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  • A Method of Arrival Time Estimation Based on Energy Mean Detection
  • A Method of Arrival Time Estimation Based on Energy Mean Detection
  • A Method of Arrival Time Estimation Based on Energy Mean Detection

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Embodiment Construction

[0018] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0019] The embodiment of the present invention relates to a time-of-arrival estimation method based on energy mean value detection. This method uses multiple pulses for time averaging, which reduces the interference caused by environmental noise, and then performs energy analysis on the time-averaged received signal. Block analysis, solve the TMMMR value, then set the normalization threshold, and finally get the TOA estimate, s...

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Abstract

The invention relates to a time of arrival estimation method based on energy mean detection. The method comprises the steps of carrying out time averaging on multiple pulse receiving signals, thereby obtaining frame synchronous ultra wide band receiving signals; obtaining energy signals through a square-law detector, and sampling the energy signals, thereby obtaining an energy sampling sequence of the receiving signals; obtaining a maximum and minimum to mean energy sample ratio of the receiving signal after time averaging according to the obtained energy sampling sequence, obtaining an optimum normalization threshold through a function relationship between the maximum and minimum to mean energy sample ratio and the optimum normalization threshold, and determining a judgment threshold; and selecting a middle position of an energy block first exceeding the judgment threshold as a time of arrival estimation value. According to the method, the high performance can be realized in a working signal to noise ratio range.

Description

technical field [0001] The invention relates to the technical field of wireless positioning, in particular to a time-of-arrival estimation method based on energy mean value detection. Background technique [0002] UWB has the advantages of low system complexity, strong penetrating ability and high time resolution, so that it can achieve high positioning accuracy in wireless positioning technology and has attracted more and more attention. Due to its own Ghz bandwidth, ultra-wideband signals do not need to be modulated during transmission, that is, signal transmission can be carried out without a carrier, which reduces the cost of transmission, and at the same time, the positioning accuracy reaches centimeter level. It is other positioning technologies, such as Bluetooth, zigbee and WiFi Waiting can't be matched. [0003] In UWB positioning technology, there are mainly three estimation methods based on AOA, RSSI and TOA / TDOA. There are mainly three existing TOA estimation m...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W64/00G01S5/14
CPCG01S5/14H04W64/006
Inventor 罗珊珊李强熊勇王营冠
Owner SHANGHAI INTERNET OF THINGS
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