我想问一下 I Beacon 广告，尤其是 Tx Power。我使用了两个BLE模块HM10和HM11。我做了一个作为 ibeacon (HM10)。另一个用于连接和收听HM10广播。我使用与 HM11 绑定的 MCU ATmega32 AVR，并使用 scanf 函数读取广播。我想提取最后一个字节（Tx Power）。我想用 AVR 编程测量距离。你能告诉我算法吗？
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A bit late but hopefully useful to others. I have given up on Apple's "Accuracy" number; as @davidyoung points out, different devices will have different signal gains. Now I am not an engineer but more of a math and statistics person, so I have gone down the route of "fingerprinting" an indoor space instead. Essentially I read all RSSI from all beacons installed in a certain "venue". Some might not be within reach and therefore I just assume, in such cases, an RSSI of -95 dBm (which seems to be the floor past which a signal is not read any more). Such constituted array has the same beacons in the same positions at all times (even across app launches). I compute a 5 seconds moving average for each beacon (so a I se 5 arrays to do that). The resulting avg array is then shifted up by 95 units and normalised so that the sum of all of its values is one. If you want to tag an an indoor "point" you collect many of these normalised average arrays on that specific spot. I go ahead and construct a database of "spots". To forecast your proximity to any spot in a database you simply compute a quadratic distance of your current reading and the all of the fingerprints in the database.
Which beacons to use? At least class 2 in power. How many? At least a couple per room (put them in two adjacent corners, on the ceiling or high up).
The last step that you need to do is match the fingerprints with an x,y coordinate on your map. I never did this step, because I am mainly interested in proximity applications and not fully fingerprint and indoor space.
Perhaps the discussion above will serve you as a guidance on a technique that is used by many indoor location companies.
Disclosure: I have recently open sourced my code doing the above calculations.
于 2015-12-16T13:08:58.080 回答