A WSN node location method based on rss and ranging unbiased estimation
A technology of node positioning and partial estimation, which is applied in wireless communication, electrical components, etc., can solve the problems that the ranging deviation cannot be eliminated essentially, the analysis is insufficient, etc., and achieve the effect of moderate complexity and improved accuracy
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specific Embodiment approach 1
[0031] Specific embodiment one: a kind of WSN node localization method based on RSS and ranging unbiased estimation of this embodiment, specifically is prepared according to the following steps:
[0032] Step 1. Pre-deploy M beacon nodes in the working environment of the sensor network; assume any unknown node U in the working environment of the sensor network = (x, y), and let U receive information from the beacon node B i The coordinates of the signal are x i ,y i , namely B i It is visible to the unknown node U, i=1, 2,..., N, N≤M; wherein, N represents the number of beacon nodes visible to the unknown node U;
[0033] Step 2. According to the general signal propagation model, calculate the distance between the unknown node and the beacon node B under the influence of Gaussian noise n i distance Among them, at the distance from the beacon node d 0 Set the reference node at , and the reference node receives the beacon node B i The signal power is P i (d 0 ); unknown...
specific Embodiment approach 2
[0052] Specific embodiment 2: The difference between this embodiment and specific embodiment 1 is that in step 2, according to the general signal propagation model, under the influence of noise n, the unknown node and the beacon node B i distance The specific process is:
[0053] P(d)=P(d 0 )-10αlg(d / d 0 ) (7)
[0054] Among them, d 0 is the distance from the reference point to the beacon node, take d 0 =1m; n is the mean value is 0, and the variance is Gaussian noise; d is the distance between the unknown node and the beacon node; without the influence of Gaussian noise, the signal power received by the unknown node from the beacon node is P(d);
[0055] According to the general signal propagation model in formula (7), the unknown node U and the beacon node B i the distance is d i , in the case of noise, the signal power received by the unknown node from the beacon node is P(d)=P i (d i )+n, P i (d 0 ) and v i Substitute into formula (7) to get:
[0056] P i ...
specific Embodiment approach 3
[0060] Specific implementation mode three: the difference between this implementation mode and specific implementation mode one or two is: in step three, v in step two i Perform an expectation analysis to get The specific process is:
[0061] Obtained according to formula (8),
[0062]
[0063] definition n is the mean of 0 and the variance of Gaussian noise,
[0064] For unknown node U and beacon node B i The ranging distance between v i , satisfying the following probability density function:
[0065]
[0066] then v i The expected value E(v i )for:
[0067]
[0068] Wherein, i=1,2,...,N. Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.
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