How to Use GNSS Modules to Create Location-Aware Smart City Solutions

Location-aware services (LAS) in smart cities are being deployed across various areas, including government services, transport, traffic management, energy, healthcare, and water and waste, and creating safer, more sustainable, and better-connected cities. There is often a need to understand the distances between nearby devices in these applications. The demand for position-based capability using multi-constellation global navigation satellite system (GNSS) receivers for Europe’s Galileo, the USA’s GPS, Russia’s GLONASS, and China’s BeiDou navigation satellite systems is growing in LAS applications. The benefits of using multi-constellation GNSS receivers include; better availability of the position, navigation, and timing (PNT) signals, increased accuracy and integrity, and improved robustness. But developing multi-constellation receivers is a complex and time-consuming activity.

This article reviews important system design considerations when using multi-constellation GNSS receivers before presenting GNSS platforms and development environments from u-blox, Microchip Technology, MikroElektronika, Thales, and Arduino for the efficient and cost-effective development of location-aware smart city applications.

Improvements in GNSS technology, especially reduced power requirements, have been instrumental in the increased use of the GNSS and the proliferation of LAS in smart city applications. The GNSS receiver power consumption reduction has been from 120 milliWatts (mW) in 2010 to 25 mW in 2020 (Figure 1). In fact, GNSS receiver power demand has declined faster than the power needs of most other LAS system components. Older GNSS technologies were power-hungry compared with the other system elements. Today, GNSS power needs are often only a single-digit percentage of the overall power budget.

Figure 1: GNSS receiver power consumption has declined from 120 mW in 2010 to 25 mW in 2020. (Image source: u-blox)

Power consumption challenges

While GNSS receiver power consumption has declined dramatically, the complexities of getting the optimal power/performance solution have multiplied. Not every LAS design needs continuous GNSS position estimations or high levels of position accuracy. Designers have various tools to optimize GNSS performance and power consumption, including hardware optimization and firmware-based approaches.

The use of low-power components, especially low-noise RF amplifiers (LNAs), oscillators, and real-time clocks (RTCs), is the first step in developing energy-efficient GNSS solutions. The choice between active and passive antennas is a good example. Passive antennas are lower in cost and more efficient but don’t meet the needs of every application. An active antenna may be a good choice in urban canyons, inside buildings, or other locations with poor signal strength. The LNA in the active antenna significantly increases the ability to receive weak signals but also consumes significant amounts of power. When power consumption is critical, and antenna size is not as important, a larger passive antenna can often provide the same performance as a smaller active antenna while still providing high position availability and accuracy levels.

Most GNSS receivers can provide update rates of 10 Hertz (Hz) or higher, but most LAS applications work well with much slower and less power-consuming update rates. Selecting the optimal update rate can have the largest impact on power consumption. In addition to the hardware-based considerations, designers have a range of firmware tools available when optimizing power consumption, including update rates, the number of concurrently tracked GNSS constellations, assisted GNSS, and a variety of power-saving modes (Figure 2).

Figure 2: In addition to using the most efficient hardware solution, designers have several firmware tools to optimize GNSS performance and energy consumption. (Image source: u-blox)

It may be necessary to track multiple GNSS constellations concurrently in challenging environments. While receiving signals using various bands can ensure a robust position determination, it also increases power consumption. It’s important to understand the specific operating environment, especially how open the sky view is, and use the minimum number of GNSS signals required to support the needs of the particular LAS application.

Turning the GNSS function off saves the most energy but results in a cold start every time it’s turned on. The time to first fix (TTFF) for a cold start can be 30 seconds, or longer, depending on the availability and strength of the GNSS signals and the size and placement of the antenna. Assisted GNSS can reduce the TTFF while still providing accurate information. Assisted GNSS can be implemented in several ways, including the current and predicted satellite location and timing parameters (called ‘ephemeris data’), almanac, and accurate time and satellite status correction data for the satellite systems downloaded over the internet in real-time or at intervals of up to several days. Some GNSS receivers have an autonomous mode that internally calculates GNSS orbit predictions, eliminating the need for external data and connectivity. However, using autonomous mode can require that the receiver be turned on periodically to download current ephemeris data.

Power save modes

In addition to connectivity options such as assisted GNSS, many GNSS receivers enable designers to select from a range of tradeoffs between update rates and power consumption, including continuous tracking, cyclic tracking, on/off operation, and snapshot positioning (Figure 3). Selecting the optimal tracking mode is another important consideration when defining the performance of a specific application. If operating conditions change, making the optimal power-saving mode unavailable, the system should automatically switch to the next most energy-saving mode to ensure continuous functionality.

Figure 3: Energy-saving operating modes need to be matched with required update rates to optimize GNSS system performance. (Image source: u-blox)

Continuous tracking is suited for applications that require a few updates per second. The GNSS receiver acquires its position in this mode, establishes a position fix, downloads almanac, and ephemeris data, and then switches to tracking mode to reduce power consumption.

Cyclic tracking involves several seconds in between position updates and is useful when the signals and/or the antennas are sufficiently large to ensure position signals are accessible as needed. Additional power savings can be achieved if the tracking does not require the acquisition of new satellites.

On/Off operation involves switching between acquisition/tracing activities and sleep mode. The time in sleep is typically several minutes and on/off operation requires strong GNSS signals to minimize the TTFF and, therefore, the power consumption following each sleep period.

Snapshot positioning saves power by using the GNSS receiver for local signal processing combined with cloud computing resources for the more compute-intensive position estimation processing. When an internet connection is available, snapshot positioning can reduce GNSS receiver power consumption by a factor of ten. This solution can be an effective power-saving strategy when only a few position updates per day are needed.

Embedded antenna supports GNSS augmentation

Designers can turn to the SAM-M8Q patch antenna module from u-blox for systems that benefit from the concurrent reception of GPS, Galileo, and GLONASS GNSS signals (Figure 4). Using three constellations at once results in high position accuracy in challenging environments such as urban canyons or when receiving weak signals. To speed positioning and improve accuracy, the SAM-M8Q supports augmentation functions, including a quasi-zenith satellite system (QZSS), GPS aided GEO augmented navigation (GAGAN), and indoor messaging system (IMES), together with wide area augmentation system (WAAS), European geostationary navigation overlay service (EGNOS), and the MTSAT satellite augmentation system (MSAS).

Figure 4: The SAM-M8Q module supports concurrent reception of up to three GNSS sources (GPS, Galileo, GLONASS). (Image source: u-blox)

The SAM-M8Q module can also use the u-blox AssistNow assistance service that provides GNSS broadcast parameters, including ephemeris data, almanac, plus time or rough position, to reduce the TTFF significantly. The extended validity of AssistNow Offline data (up to 35 days) and AssistNow Autonomous data (up to 3 days) supports faster TTFF even after an extended time.

This internet of things (IoT) Google Cloud development platform provides a simple way to connect and secure PIC MCU-based applications. GNSS 4 click from MikroElektronika contains a SAM-M8Q module and is designed with the PIC®-IoT WG Development Board from Microchip Technology to speed the development of LAS smart city applications (Figure 5). The PIC-IoT WG development board provides Google Cloud IoT users a way to accelerate the development of secure cloud-connected applications. In addition, the PIC-IoT WG board provides designers with analytics and machine learning tools.

Figure 5: The GNSS 4 click board carries the SAM-M8Q patch antenna module from u-blox. (Image source: DigiKey)

Multi-constellation GNSS plus wireless connectivity

For small LAS devices such as trackers that can benefit from multi-constellation GNSS support (GPS/Galileo/ GLONASS) and global LPWAN LTE connectivity from a single module leveraging Rel. 14-second generation Cat. M1/NB1/NB2, designers can turn to the Cinterion TX62 module from Thales (Figure 6). Solution size can be further optimized using the module’s flexible architecture that supports running applications using a host processor or inside the module using the integrated processor. The TX62 supports 3GPP power saving mode (PSM) and extended discontinuous reception (eDRx) for power-sensitive applications. PSM sleep times tend to be much longer than eDRX. These longer sleep times allow the device to enter into a deeper, lower power sleep mode than eDRX. PSM sleep power is under ten microamps, while eDRX sleep power is up to 30 microamps.

Figure 6: The TX62 IoT module supports LTE-M, NB1, and NB2 communications and multi-constellation GNSS. (Image source: Thales)

TX62 security features include secure key storage and certificate handling to support trustful enrollment in cloud platforms while protecting the device and data, plus trusted identities pre-integrated into the root of the TX62 during manufacturing. When needed, designers can specify an optional integrated eSIM that can simplify logistics and manufacturing processes and improve flexibility in the field through dynamic subscription updates and remote provisioning.

LAS development in Arduino Portenta H7 applications is simplified using the Portenta Cat. M1/NB IoT GNSS Shield (Figure 7). The shield combines the edge computing power of the Portenta H7 with the connectivity of the TX62 to enable the development of LAS asset tracking and remote monitoring in smart city applications as well as industrial, agriculture, utility, and other areas. The basic Portenta Cat. M1/NB IoT GNSS Shield does not include a GSM/UMTS antenna. Instead of searching for a compatible antenna, designers can use the Arduino dipole pentaband waterproof antenna.

Figure 7: The Portenta CAT.M1/NB IoT GNSS Shield includes the TX62-W IoT module (large yellow square). (Image source: Arduino)

Additional benefits of the Portenta CAT.M1/NB IoT GNSS shield include:

• Ability to change connectivity without changing the board
• Add positioning plus NB-IoT, CAT.M1 any Portenta-based design
• Significantly lowered communication bandwidth requirements in IoT devices
• Compact 66 mm x 25.4 mm format
• -40°C to +85°C operation (-104°F to 185°F)

Summary

Advances in low-power and high-performance GNSS technology are factors driving the growth of LAS smart city applications. However, simply using the most energy-efficient hardware is only the starting point; it’s equally important to optimize the firmware to arrive at an optimal and energy-efficient solution. There are numerous combinations of hardware and firmware available to choose from when developing GNSS-based LAS applications and designers can turn to a variety of eval tools to speed the development process.