WLAN (Wireless Local Area Network) indoor neighbourhood matching positioning method based on autocorrelation filtering
A positioning method and autocorrelation technology, applied in electrical components, wireless communication, network topology, etc., can solve the problems of location fingerprint database dynamic change position dependence, etc., to ensure positioning accuracy and real-time performance, and improve positioning accuracy
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specific Embodiment approach 1
[0015] Specific implementation mode 1: The specific steps of the WLAN indoor proximity matching positioning method based on autocorrelation filtering are as follows:
[0016] Step 1, in the off-line collection phase, uniformly mark the reference point RP (Reference Point) position in the target positioning area, in the present invention, the distance interval between adjacent reference points is 1m, WLAN wireless network access point AP (Access Point) , to ensure that any position in the target positioning area can receive the signal strength from at least one AP;
[0017] Step 2. At each reference point, the signal strengths from different APs are collected at a sampling rate of 2 samples / second, and stored in the strength fingerprint sample sets corresponding to different reference point positions;
[0018] Step 3: In the offline correction stage, first use the autocorrelation characteristics of the continuous intensity signal, according to the correlation coefficient thresh...
specific Embodiment approach 2
[0021] Specific embodiment two: WLAN indoor adjacent matching location method based on autocorrelation filtering, it is characterized in that step 3 comprises:
[0022] Sub-step 1: Set the reference point R i =(x i ,y i ), (i=1,...,N RP The set of intensity fingerprint samples collected at ) is expressed as Among them, N RP Indicates the total number of reference points in the positioning area, x i and y i Respectively represent R i X and Y coordinates, N SS Indicates the total number of samples contained in the intensity fingerprint sample set, x(j), (j=1,...,N SS ) represents the jth sample in the intensity fingerprint sample set;
[0023] Sub-step 2: Use the formula: Calculate the autocorrelation coefficient for each set of intensity fingerprint samples;
[0024] Sub-step 3: According to the correlation coefficient threshold Judging whether there are singular strength samples in the original signal strength fingerprint sample set, if for any delay number, the...
specific Embodiment approach 3
[0029] Specific embodiment three: WLAN indoor proximity matching positioning method based on autocorrelation filtering, characterized in that the received signal strength RSS (Radio Signal Strength) is greater than the sensitivity of the receiving terminal -90dBm. Other components and connections are the same as those in Embodiment 1.
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