Category: DirectionFinding

Bluetooth 5.1 Angle-of-Arrival Antenna Array Design

There’s new research from University of Porto, Portugal on Design and Experimental Evaluation of a Bluetooth 5.1 Antenna Array for Angle-of-Arrival Estimation.

Experiments were conducted on a circular antenna array in an anechoic chamber and in a real-world environment to evaluate the quality of the retrieved data. The setup included four beacons advertising a Constant Tone Extension (CTE).

The researchers used a combination of ways to process the data including a non-linear recursive least square method, an unscented Kalman filter, non-linear least square curve fitting, a Gaussian filter and Multiple Signal Classification (MUSIC).

The paper explains how reducing computational complexity is critical in order to achieve real-time processing on edge devices. Accuracy is affected by noise originating from multi-path effects, differences in oscillators between transmitter and receiver, behaviour of the RF switch and slight variations in impedances of the antenna tracks between antenna pairs. There’s much more noise in the real-world environment than in the anechoic chamber.

The researchers conclude that they found it difficult to reduce the error in the obtained phase measurements and identify which packets were reflections.

This paper demonstrates that processing of AoA IQ data is non-trivial. Processing in real-time for a more than a few assets is a challenge. This is why, while many AoA reference kits’ can be used to demonstrate AoA, the accompanying software often isn’t scalable to the required number of assets.

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Introduction to Bluetooth Direction Finding

The Bluetooth SIG, the owner of Bluetooth standards, has a useful video introduction to Bluetooth® Location Services and High-Accuracy Direction Finding. It’s the 4th video from Embedded World 2020. Strangely, you need to view direct from the Bluetooth SIG site because this video isn’t available direct from Vimeo.

Martin Woolley, Senior Developer Relations Manager, provides a high level overview and explains how direction finding differs to positioning using RSSI signal strength. He describes how Bluetooth Angle of Arrival (AoA) and Angle of Departure (AoD) make use of multiple angles to provide accurate location.

Martin dives deeper into direction finding theory and phase sampling. He explains how Bluetooth uses Frequency Shift Keying (FSK) of the radio carrier signal that necessitates use of a Constant Tone Extension (CTE) to enable direction finding. It’s explained how Bluetooth Controller IQ sampling fits into the Bluetooth stack.

View G2 AoA Gateway Kit

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New Silicon Labs Bluetooth Direction Finding Design

Silicon Labs has a new range of Bluetooth System on a Chip (SoC), the EFR32BG22 (BG22) boasting power efficiency with up to ten years on a coin cell battery. It supports the Bluetooth 5.2 specification, Bluetooth direction finding and Bluetooth mesh. The Bluetooth direction finding provides Bluetooth Angle of Arrival (AoA) and Angle of Departure (AoD) capabilities with sub-one-meter location accuracy.

Silicon Labs have announced a new direction finding kit with a 4×4 antenna array board for evaluation and development. Note that this is a reference design rather than a product that can be rolled out.

The antenna array design and user guide make interesting reading if you want to learn about AoA hardware design.

Many of our customers have misconceptions about direction finding reference design kits. They exist to prove direction finding and are intended as a base design on which to create your own custom hardware using the same components. They aren’t intended for rollout as they generally aren’t physically robust and also don’t have software that will scale to more than a few assets.

Instead, see the Minew AoA kit for a production product.

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Passive Human Sensing Using Bluetooth

There’s new research from University of Catania, Italy on A Perspective on Passive Human Sensing with Bluetooth. The research identifies and discusses the factors and operating conditions that can result in varying accuracy.

The paper explains the advantages of Bluetooth over WiFi for passive human sensing. It also discusses the advantages and disadvantages of RFID, VLC, LoRa and LTE. The paper seeks to address the lack of search papers on considering Bluetooth as opposed to WiFi for detecting human presence.

The paper describes how human presence can influence a wireless signal and covers Bluetooth Direction Finding. It explains how Bluetooth is better suited for human detection because it is less subject to electromagnetic noise.

It’s mentioned how signals received on different Bluetooth different channels have different noise and attenuation characteristics:

“Another issue often highlighted in the literature is the impossibility of independently extracting the RSSI signal values from each advertising channel of the BLE beacons. The BLE beacons need to be modified at the hardware or firmware level in order to transmit on a certain preset channel and to allow the researcher to discriminate the variation in the signal due to the presence of a human body from other fading effects.”

What isn’t mentioned in the paper is that Bluetooth Direction Finding requires analysis of the IQ data rather than RSSI. This IQ data also varies depending on the Bluetooth channel. Direction finding receivers can (and must) independently extract and process the channel specific data.

Using AI Machine Learning with Bluetooth Angle of Arrival (AoA)

There’s new research from Universities in Piraeus, Greece and Berlin, Germany, together with U-Blox AG in Switzerland who create Bluetooth Angle of Arrival prototyping boards on Deep Learning-Based Indoor Localization Using Multi-View BLE Signal.

Processing of Bluetooth Angle of Arrival usually requires radiogoniometry spectral analysis of radio in-phase and quadrature-phase (IQ) signals in order to then determine location by triangulation. Instead, this paper proposes machine learning of IQ and signal strength (RSSI) data from multiple anchor points to determine location. AoA processing also uses distributed processing across the anchors to improve performance.

The developed machine learning models were found to be robust against modifications of room furniture configurations and materials and it’s therefore expected that they have high re-usability (machine learning generalisation) potential. The system achieved a localization accuracy of 70cm.

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Bluetooth Myths and Facts

There’s a useful new webinar at the Bluetooth SIG on The Myths & Facts About Bluetooth® Technology as a Positioning Radio. Fabio Belloni from Quuppa explains the main Bluetooth myths and facts:

  • Performance – There are misconceptions about accuracy, latency and reliability brought over from older systems using only received signal strength (RSSI). Newer systems based on Bluetooth direction finding provide much improved performance.
  • Communication Range & Coverage Area – People incorrectly think Bluetooth is a short range 10m – 15m technology. This isn’t so. Long range beacons can transmit up to 1.5Km and can work up to 100m in location finding scenarios.
  • Multipath Propagation – It’s wrongly perceived that Bluetooth is poor in harsh environments. Bluetooth is, in fact, designed for factory floor and additionally newer AoA direction finding can use spectral analysis to reduce the affect of radio reflections.

Gabriel Desjardins from Broadcom mentions how location technologies have overcome the peak of inflated expectations caused by UWB and are now in the plateau of productivity provided by Bluetooth LE.

Andrew Zignani shows the results of a survey on RTLS from 213 C-Level decision makers across five main verticals. Only 13% of businesses have already deployed RTLS and there will be a increased uptake over the next 5 years. Technology fragmentation and operational/maintenance cost are incorrectly seen as the barriers to adoption. The new Bluetooth AoA direction finding standard is easing fragmentation. The maintenance cost is actually very low compared to the ROI in most scenarios. Most want beacon battery life to be 90+ days and cost to be $11-$20 that are easily achievable with today’s beacons.

Angle of Arrival Accuracy Improvement

There’s new research from Department of Electrical and Information Engineering, Bari, Italy on A Linear Technique for Artifacts Correction and Compensation in Phase Interferometric Angle of Arrival Estimation that can be used with Bluetooth AoA Direction Finding.

The paper first discusses the main causes of error in AoA systems. This includes signal path length mismatches as avoided by the CoreHW AoA Hardware printed circuit board (PCB) tracks and mutual RF coupling effects that act on the antenna array.

The researchers devised and proved a technique to process IQ data to reduce systematic errors and first-order (linear) coupling effects. After a calibration phase they manged to reduce average absolute errors by more than a half in one test case more than a quarter in a second case.

Research on techniques such as this will make Bluetooth direction finding even more accurate.

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Managing Bluetooth LE Advertising Congestion

Bluetooth LE advertising congestion happens when there are too many Bluetooth devices in an area. As we will show, this rarely happens but with new Bluetooth technologies this situation is becoming more likely. We provide some ways to mitigate congestion.

Bluetooth LE advertising transmits periodically the period of which is configurable from typically 100ms to about 10 seconds.

Bluetooth LE advertising (from Bluetooth SIG)

If two Bluetooth devices happen to transmit at the same time, it’s like two people shouting at the same time. The signal is corrupted, the receiver can’t make sense of the signal and it is lost. This usually doesn’t matter because it’s likely the signal is seen the next time it is sent. The random advDelay in the above diagram ensures that the two sends don’t clash again. It’s very unlikely advertisers clash in the first instance because the transmit duration is very small compared to the advertising period. The above diagram isn’t to scale. Here’s an oscilloscope trace showing some real timing:

The advertising duration is very small, of the order of 1 to 2 ms (milliseconds). Advertising is also sent three times, on three different radio frequencies, so that if one is blocked, the radio signal might be heard on one of the others. All this means that advertising collisions rarely occur.

However, there are some newer Bluetooth protocols that as they are starting to roll out, are making collisisons more likely:

  • Bluetooth 5 advertising extensions – This allows advertising of more data, that takes longer than the typical 1 to 2 ms and hence increases congestion.
  • Bluetooth longer range – This transmits further thus effectively increasing the number of beacons advertising in a given area.
  • Bluetooth Mesh – This works by having relay beacons listen and re-transmit advertising, usually several times, to improve reliability.
  • Bluetooth direction finding – This also has longer advertising to send a constant tone extension (CTE) that is received by AoA hardware. However, of more affect is advertising more frequently. While beacons on assets used to advertise typically every second or longer, direction finding tends to use faster advertising to improve latency.

You can check how many devices are advertising by using a scanning app on Android. We recommend Nordic Semiconductor’s nRF Connect because it can decode the latest Bluetooth protocols. Use Android for full visibility because Apple made the poor design decision to obfuscate iBeacon advertising to coerce developers to only use the Apple iBeacon-specific APIs. Apple also hides devices’ MAC addresses making them more difficult to physically identify.

If you have a problem with congestion you might be tempted to increase the transmission power or advertise more often to increase the chances of being seen. However, this is counter-productive because you will be increasing congestion, especially if your devices are the main contributor to the congestion.

Instead:

  • Lower the transmit power so that beacons cover a smaller area. You can fine tune this using nRF Connect to measure the distance you need rather than needlessly advertising further. This will also conserve battery life.
  • Increase the advertising period to make collisions less likely.
  • Increase the receiver scanning period to make detections more likely.
  • Seek out and remove unwanted devices advertising too frequently, such as fitness devices, smartphones, displays and even cars.

Need more help? Consider our consultancy services.

CoreHW AoA Hardware

CoreHW in Finland is a new entrant in the Bluetooth direction finding ecosystem. Their main product is the CHW10x0 chip that supports switching of complex antenna arrays needed for Bluetooth direction finding. It allows designs with only one component where three to five are usually required. The switch has a fast settling time for RF signals and a good phase balance between antenna ports providing better position accuracy.

CoreHW also has reference antenna arrays and 2D software for angle and position estimation to shorten time-to-market for AoA locator and AoD beacon manufacturers. They have a demo kit including 4 locators, 2 tags, a CorePatch antenna array board with CHW1010 chip, a Bluetooth T5.1 chip for IQ sampling and a USB interface (Ethernet) to connect locators with a Windows PC.

The CoreHW reference boards have some intriguing Medusa-type printed circuit board (PCB) tracks, presumably to keep the track length the same to each antenna to normalise RF signal delays.

We look forward to seeing CoreHW components in their customers’ production devices.