How to calculate distance using BLE beacons if the user is moving in a vehicle with 2-15kmph speed?Also,if the distance won't give me accurate results is there any other mechanism with the help of which I can calculate the nearest beacon.The default implementation does not give me proper results as there is a 20sec lag in distance estimates.
Secondly,in which cases should ARMA filter be used.
Beacon distance estimates are only estimates, so you must set accuracy expectations accordingly. In order to reduce noise on radio signal levels, many samples are averaged over a period of time.
Figuring out the appropriate averaging time depends on the use case. As you have noted, the Android Beacon Library uses a 20 second running average by default. This gives a distance estimate based on where the vehicle was on average over the past 20 seconds.
For a vehicle going up to 15km/hour (~5 meters / sec) with a beacon transmission radius of 50 meters, it will be in range of the beacon for a maximum of 10 seconds. How many distance measurements do you need to get? If one is enough, average over 10 seconds. If you need more, set the period even shorter.
Understand that reducing the sample interval will add more noise error to the distance estimates, because you will have fewer statistical samples to work with. A few things you can do to make the most of the samples you do get:
Set the beacon to advertise as frequently as possible. Some beacons advertise at 1Hz or less to save battery. This leads to poor distance estimates. Increase it to 10Hz or more if possible.
Turn off bluetooth configurability/connectability on your beacon. Some Android devices will only allow one signal level sample per BLE scan (1.1 secs by default in the library) in connectable mode. This can lose you 90% of your samples at 10 Hz.
Configure the beacon transmitter to be on its highest power setting and calibrate it properly. Stronger signals have a higher signal to noise ratio, giving better distance estimates.
The ARMA filter uses a nondeterministic sample interval based on % change in each sample. It is more appropriate for use cases with slow moving beacon receivers.
Related
I'm working on beacon mapping app when a beacon enters in 2 meters range i have to call web service but by using this library it's showing wrong distance if beacon is in 5m range then also it's showing 1.5 something
if (oneBeacon.getDistance() <= 2) {
final String distanceString = String.valueOf(major.toString() +
middle.toString() + minorString.toString());
beaconList.add(distanceString);
}
A few tips:
Understand that beacon distance estimates are very rough and will never be exact. You must set your expectations appropriately. At 1 meter actual distance, estimates of 0.5-2 meters are typical. Obstructions and reflections affect this.
You must calibrate your beacon so that the 1m expected signal level is transmitted inside the packet. This involves measuring the signal level at 1m then spring this "measured power" inside your beacon. Your beacon supplier should provide you with instructions on how to set this.
On Android, a very fragmented hardware base means big variations in Bluetooth chips, antennas and phone cases all of which affect the distance estimate on a device to device basis. If you know your target devices, you can refine the distance formula for these devices. This is a more complex procedure, so only worth doing if (2) does not give you the results described in (1).
Scenario: People wearing beacons are coming from the airport and I am standing at an exit gateway.
Requirement:
I only want to view persons within 3-meter.
I want to mark the person leaving and for ease I want them to view in a sorted(according to distance) way in my Android application.
Currently facing inconsistency in the distance emitted(Eddystone) by beacons.
Please suggest how to remove noise and get an accurate distance of the beacon or please suggest if there is any other way to do this task.
It is normal for distance estimates to fluctuate as radio noise alters the estimate. Set your expectations appropriately, and this is OK. Larger distance estimates will fluctuate more as there is more noise than signal in the input to the distance estimating algorithm.
If sorting by distance in the UI, your best bet for stability is to first convert the distance to a range of distances (e.g. 0-0.5 meters, 0.5-1 meters,1-3 meters, 3-5 meters, 5-10 meters, 10+ meters). You can then sort the list to be displayed in the UI by distance range and MAC address. This will keep the list much more stable.
There will still be variations as beacons move up and down the list, but much less so than when sorting by raw distance estimates.
You can also reduce the fluctuation in your distance estimate by increasing your beacon transmission rate, increasing the power of the transmitter, and adjusting your beacon scanner to average your distance estimate over a longer interval.
I'm using the altbeacon library to implement an indoor navigation application using ibks beacons, but my problem is that I want a fast scan so I used the setSampleExpiration method and set it to 10 seconds, but now the distances are imprecise. How can I have a good precision with a faster scan ?
When using Bluetooth LE to get distance estimates there is always a tradeoff between accuracy and the number of statistical samples. Because there is a lot of noise on RSSI, you need lots of samples to filter it out.
Reducing the sampling time from the default of 20 seconds to 10 seconds will make estimates change more quickly, but at the cost of this accuracy.
One thing you can do is increase the number of signal measurements. If you can increase the advertising rate on the ibks beacon (for example from 1 Hz to 10 Hz) then you will have more samples and get better estimates.
For my project I need to estimate the distance between a Smartphone and a bluetooth module. The Estimation doesn't have to be very precise. I only need to determine the distance with a margin of error of about 50cm.
I did test the RSSI of two bluetooth modules at distance-steps of 10 cm. I measured the RSSI 5 times for each step and got the average of the 5 measurements. The averages are shown in the graph below:
The red and blue lines resemble the two Bluetooth modules. You can see that the results are not very linear. One of the reasons for this is interference, so i searched for ways to tackle the interference issue. Two ways i found are:
Signal Noise Ratio(SNR): Understanding ibeacon distancing
ratio of the iBeacon signal strength (rssi) over the calibrated transmitter power (txPower). The txPower is the known measured signal strength in rssi at 1 meter away: http://www.princeton.edu/~achaney/tmve/wiki100k/docs/Signal-to-noise_ratio.html
However i don't really understand how the above techniques would be used to get more accuracy. For SNR i need the Noise value, how do i even get the Noise value?
For ratio rssi/txPower, I can get the txPower by simply measuring the rssi at 1 meter from the module. So I know all the needed values. But I don't know what to do from here on out. How do i use these values to get a more accurate distance estimations?
Are there any other techniques i can use to improve accuracy?
You are running into the practical limitations on this technology. Getting estimation accuracy of +/- 50 cm may be possible under ideal conditions at short distances (under 2 meters) not at long distances of over 10 meters.
I wrote a longer blog post about the limits 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 know what part of a single RSSI measurement comes from signal and what part comes from noise. You can take an average over many samples, which partially removes noise if the transmitter and receiver are stationary over the sample interval.
The techniques you ask about do work to give you distance estimate, but they have the limitations of the technology described above.
I have couple of questions regarding the Radius networks Beacon.
How can we get the accurate distance between android devices and
beacon? So far the distance we're getting through
"android-beacon-library" is fluctuating.
How can we limit the beacon's transmission radius, say allowing
beacon to transmit only for 5 meters or to 20 cms ?
Please find the image with beacon distance reading for various devices (Moto g , Nexus 5 , Nexus 4 and iPhone 5s)
You will always see fluctuation on beacon distance estimates, so you have to set your expectations appropriately. Beacon distance estimating works by starting with a measurement of the radio signal strength using the bluetooth radio on the mobile device. A stronger signal means that the beacon is closer, where a weaker signal means the beacon is further away. The beacon transmits a reference value of its expected signal strength at 1 meter, saying in effect "If you are one meter away, you should see my signal level as -56 dBm". A formula inside the mobile phone then tries to make a guess of how far it is away based on the signal level at any given time. If the signal is a little bit weaker than -56dBm, such as -65dBm, the formula might estimate that the distance is 2.5 meters.
This technique is imperfect, and there are several reasons for fluctuation:
There is always background radio noise (like the static on an old AM radio) which causes individual signal strength measurements to vary.
There is error on the analog to digital converter inside the bluetooth radio, which also causes individual signal strength measurements to vary.
The bluetooth radio waves reflect off of some objects and are absorbed by others, making the actual signal strength change at different positions the same distance away, and when other objects in the vicinity move around.
The antenna pattern on both the transmitter and the receiver are not perfectly spherical. This means that when you rotate your phone or the beacon, you will see a slightly different signal level.
There are a few things you can do to minimize the error:
Use a beacon that transmits as frequently as possible, preferably at 10Hz or more. More transmissions mean more statistical samples of the signal level, which when averaged together help mitigate errors from sources 1 and 2 above.
Use as high of a transmitter power setting on your beacon as possible. The stronger the signal, the lower the noise level will be (relatively speaking) from source 1 above.
When possible, place your beacons where there is a clear line of sight to the receiving devices. Overhead often works best.
However, the best you can hope to do is reduce the variation as much as possible. You cannot eliminate it. For this reason, you must design your app so such variation is acceptable. If it helps your use case, you can also lower the beacon transmitter power so that devices only detect the beacon when they are relatively close.
Using Radius Networks' RadBeacon USB and RadBeacon Tag models, you can adjust the transmitter power using the free RadBeacon configuration app for iOS and OSX. The apps have a slider control to increase and decrease the transmitter power.
You should note, however, that by lowering the transmitter power, you will also increase the amount of variation on your distance estimates. This is because the signal to noise ratio will be lower.
Full disclosure: I am Chief Engineer for Radius Networks.
you can't really tell the distance to one beacon. That's why indoor localization is so hard.
you can't say exactly how far a beacon should transmit its signals, but on most beacons (I don't know about Radius networks) you can change the txPower / transmit power. This varies from beacon to beacon (and also depends on the environment around the beacon), so you'll have to do your own experiments to find the sweet spot.