How to improve the measurement of the distance between Bluetooth using RSSI?

Question

For my project, I need to estimate the distance between the smartphone and the Bluetooth module. The assessment does not have to be very accurate. I only need to limit the distance with an error of about 50 cm.

I checked the RSSI of two bluetooth modules at a distance of 10 cm. I measured RSSI 5 times for each step and got the average of 5 measurements. The average values ​​are shown in the graph below:

The red and blue lines resemble two Bluetooth modules. You can see that the results are not very linear. One of the reasons for this is interference, so I was looking for ways to solve the interference problem. I found two ways:

• Signal To Noise Ratio (SNR): Understanding ibeacon Distance

• iBeacon signal strength ratio (rssi) versus calibrated transmitter power (txPower). txPower - known measured signal strength in rssi at a distance of 1 meter: http://www.princeton.edu/~achaney/tmve/wiki100k/docs/Signal-to-noise_ratio.html

However, I do not understand how these methods will be used to obtain greater accuracy. For SNR, I need a Noise value, how can I get a Noise value?

For the rssi / txPower relationship, I can get txPower by simply measuring rssi at a distance of 1 meter from the module. Therefore, I know all the necessary values. But I do not know what to do next. How to use these values ​​to get more accurate distance estimates?

Are there any other methods that I can use to improve accuracy?

Answer 1

You are faced with the practical limitations of this technology. Obtaining ideal accuracy of +/- 50 cm in ideal conditions at short distances (less than 2 meters) not at large distances of more than 10 meters.

I wrote a longer border blog post here: http://developer.radiusnetworks.com/2014/12/04/fundamentals-of-beacon-ranging.html

To answer your specific questions:

• No, there is no practical way to find out which part of one RSSI measurement comes from a signal and which part comes from noise. You can take an average of many samples, which partially eliminates noise if the transmitter and receiver are stationary during the sampling interval.

• The methods you ask for work to give you an estimate of the distance, but they have the limitations of the technology described above.