计算包括信噪比的AP的距离 [英] Calculating distance of an AP including signal-to-noise ratio

问题描述

出于某种原因，一个朋友和我自己正在谈论根据从设备获得的信息(RSSI，频率，SNR等)来计算自己(笔记本电脑，电话等)与AP之间的距离..因此，在花了一些时间研究三角测量，三角测量和自由空间路径损耗之后.(在一些博客文章和Wiki的帮助下)，我能够以米为单位从AP到笔记本电脑的距离，结果比我想象的要好得多.每当我在同一个房间中或AP的视线范围内时，准确度约为一英尺.

For some reason a friend and myself were talking about calculating the distance between yourself (laptop, phone, etc.) and an AP based of the info you get from the devices (RSSI, freq, SNR, etc...). So, after spending sometime researching about trilateration, triangulation, and free-space path loss. (with the help of some blog posts and wiki) I was able to get a distance in meters from the AP to my laptop and the results were a lot better then what I thought they would be. Whenever I'm in the same room or there's a line of sight to the AP, the accuracy is about a foot.

但是，现在，我想更进一步……我希望能够考虑墙壁和其他障碍物.我认为这可能是可行的，或者至少在出现障碍时比FSPL公式能给我带来更好的结果，并且我正在考虑/研究通过计算信噪比可能实现.但是，我无法找到有关如何正确执行此操作的任何信息.这个想法总是有问题，但从来没有解决方案(或者我无法在网上找到任何东西，因为我对该主题的了解很少.大约一天的时间.).因此，在这里，我转向堆栈溢出，看看你们是否可以帮助我解决这个问题.

But now, I want to take it one step further... I want to be able to account for walls and other obstructions. I think this might be possible or at least give me a better results then the FSPL formula when there is obstructions and I was thinking/researched that it might be possible by calculating in the signal-to-noise ratio. But, I was unable to find anything on how to do this correctly. There was always a problem but never a solution to this idea (or I was unable to find anything on the web because my knowledge about this subject is very little. about a days worth.). So, here I am turning to stack overflow to see if you guys can help me out in solving this.

所以，这就是我到目前为止(在python中)....

So, this is what I have so far (in python)....

import math

freqInMHz = 2462
levelInDb = -83
SNR = -87

result = (27.55 - (20 * math.log10(freqInMHz)) + math.fabs(levelInDb)) / 20.0
meters = math.pow(10, result)

feet = meters * 3.2808

print meters
print feet

我来自美国，所以我把米和英尺都印了出来.仅仅是因为我在视觉上可以测出脚部的高度，而不是米.

I am from the US, so I printed both meters and feet out. Just because I can visually measure out feet better than I can meters.

因此，利用该公式，可以很好地找到开放空间或AP的清晰视野中的距离.如果有人有任何想法或意见，我将不胜感激.因为我目前被卡在墙上！(笑话打鼓声)

So, with that formula it does a great job of finding the distance in an open room or clear view of the AP. If anyone has any ideas or comments I would greatly appreciate it. Because I'm currently stuck on a wall! (joke punch line drums sound)

谢谢，Throdne

Thanks, Throdne

推荐答案

在这种情况下，我不确定SNR是否会如此有用，因为不同的接收器将具有不同的SNR，SNR可能相差几dB.

I am not sure if SNR can be so helpful in this case as different receivers will have different SNR which might vary by couple of dB.

SNR是在用户设备上测量的，并且随用户移动而变化.从逻辑上讲，它应该随着发送器和接收器之间距离的增加而减小.由于SNR取决于接收信号强度(RSS)和噪声(N)两个因素，因此它可能会受到各种原因的影响，例如干扰！干扰会影响N，从而影响SNR.同样，多径，散射，衍射等也会影响RSS读数.

The SNR is measured at a user device and it varies as the user moves. Logically it should decrease as the distance between the transmitter and receiver increases. Since SNR relies on two factors Received Signal Strength (RSS) and Noise (N) it can get affected by various reasons, such as interference! Interference can affect the N and as a result SNR. Also Multipath, Scattering, Diffraction and etc can affect RSS readings.

因此，如果您的公式适用于直接视线，请使用它，并尝试针对不一定基于RSS和SNR的NLOS公式.

So if your formula works for Direct line of sight use it and try to work on a formula for NLOS not necessarily based on RSS and SNR.

您可能想研究Time方法而不是RSS方法，因为它们受噪声的影响不大，甚至可以过滤出多路径.

You might wanna look into the Time methods rather than RSS methods as they don't get affected as much by noise and they can even filter out multipath.

您在代码中拥有的SNR值也不能真正成为SNR，因为它在802.11中通常不会以负数形式出现.信噪比(SNR)为负意味着您比信号噪声更大.

Also the SNR value which you have in your code it can not be really SNR as it does not appear normally as a negative number specialty in 802.11. Having a negative SNR means you have more noise than Signal.

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