【免费】低功耗、低成本GPS定位方案

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HARDWARE

METAPAPER

CORRESPONDING AUTHOR:

Jonas Beuchert

University of Oxford, UK

beuchert@robots.ox.ac.uk

KEYWORDS:

conservation technology;

wildlife tracking; satellite

navigation; low power; low

cost; open source

TO CITE THIS ARTICLE:

Beuchert, J, Matthes, A and

Rogers, A. 2023. S

napperGPS:

Open Hardware for Energy-

Efﬁcient, Low-Cost Wildlife

Location Tracking with

Snapshot GNSS. Journal

of Open Hardware, 7(1): 2,

pp. 1–13. DOI: https://doi.

org/10.5334/joh.48

SnapperGpS: Open Hardware

for Energy-Efﬁcient, Low-

Cost Wildlife Location

Tracking with Snapshot

GNSS

JONAS BEUCHERT

AMANDA MATTHES

ALEX ROGERS

*Author afﬁliations can be found in the back matter of this article

ABSTRACT

Location tracking with global navigation satellite systems (GNSS), such as GPS, is used

in many applications, including the tracking of wild animals for research. Snapshot

GNSS is a technique that only requires milliseconds of satellite signals to infer the

position of a receiver. This is ideal for low-power applications such as animal tracking.

However, there are few existing snapshot systems, none of which is open source.

To address this, we developed S

napperGpS, a fully open-source, low-cost, and low-

power location tracking system designed for wildlife tracking. S

napperGpS comprises

three parts, all of which are open-source: (i) a small, low-cost, and low-power receiver;

(ii) a web application to conﬁgure the receiver via USB; and (iii) a cloud-based platform

for processing recorded data. This paper presents the hardware side of this project.

The total component cost of the receiver is under $30, making it feasible for ﬁeld work

with restricted budgets and low recovery rates. The receiver records very short and low-

resolution samples resulting in particularly low power consumption, outperforming

existing systems. It can run for more than a year on a 40 mAh battery.

We evaluated S

napperGpS in controlled static and dynamic tests in a semi-urban

environment where it achieved median errors of 12 m. Additionally, S

napperGpS has

already been deployed for two wildlife tracking studies on sea turtles and sea birds.

METADATA OVERVIEW

Main design ﬁles: https://github.com/SnapperGPS/snappergps-pcb

Target group: biologists tracking animal movement

Skills required: PCB manufacturing and assembly (can be outsourced) – advanced;

Replication: this hardware has been replicated by every author. See section “Build

Details” for more detail.

2Beuchert et al.

Journal of Open Hardware

DOI: 10.5334/joh.48

(1) OVERVIEW

INTRODUCTION

Animal location trackers most commonly use global navigation satellite systems (GNSS)

such as the Global Positioning System (GPS). These systems use constellations of satellites

which continuously broadcast radio signals containing precise transmission timestamps and

their ephemeris data describing their orbits. A GNSS tracking device on Earth captures these

signals and infers its location from this information. A traditional GNSS receiver usually requires

more than one minute of data for a ﬁrst ﬁx (for which it needs to decode both, ephemerides

and timestamps), and at least several seconds for subsequent ﬁxes (if recently decoded

ephemerides are available) (van Diggelen 2009). However, powering the radio to capture these

signals and then the processor to calculate the location is energy expensive, resulting in the

need for large batteries with high capacity. This often makes traditional GNSS tags impractical

for tracking small animals over long deployment periods (McMahon et al. 2017).

Assisted GNSS (A-GNSS) receivers address this issue by obtaining some of the satellite data in

another way, which allows them to reduce their on-time, thereby saving energy. This is done

either by pre-loading ephemerides before the deployment or by regularly downloading them

via another connection (e.g. cellular). However, pre-loading data is only possible for short

deployments and an additional download link requires more expensive hardware and is energy

intensive.

Snapshot GNSS is another alternative GNSS concept, which, by design, has signiﬁcantly lower

energy needs, resulting in small, light-weight, energy-efﬁcient, and low-cost receivers. Instead

of capturing seconds or even minutes of the satellite signals for a ﬁx, a snapshot receiver records

just a few milliseconds. This reduces its power consumption by several orders of magnitude

compared to a traditional GNSS approach. Additionally, a snapshot GNSS device does not need

to calculate its position on-board, saving even more energy and lowering the requirements for

its computing hardware. Instead, it can just locally store the raw signal snapshots until the

deployment ends. Afterwards, the data processing can be off-loaded to the cloud.

Table 1 details pure snapshot GNSS systems that have been developed in the past. Only

BaSeBand TechnoloGieS currently offers its solution for purchase (Baseband Technologies Inc.

n.d.). It is available as a proprietary development board and, therefore, not readily available

for deployments. Only the ATS G10 module has been evaluated in a realistic scenario, but

was found to be unreliable by McMahon et al. (2017) due to battery and software failures

(Morrison n.d.). Furthermore, all existing solutions also use high sample rates and/or long

Table 1 Existing snapshot

GNSS systems.

Data from commercial GPS

front-end, not snapshot

receiver.

Rooftop with good sky

visibility.

Evaluation by McMahon et al.

(2017).

Evaluation board.

CO-GPS BASEBAND TECHNOLOGIES ETH ZÜRICH ATS G10 ULTRALITE GPS

Reference Liu et al. (2012) Baseband Technologies Inc. (n.d.) Eichelberger et al. (2019) Morrison (n.d.)

Memory 8 MBit

≤ 1,000 snapshots

4 GB

≤ 2,000,000 snapshots

2 GB

65,600 snapshots

4 GB

≤ 244,000 snapshots

Maximum

deployment

duration

1.5 years

(2 AA batteries, 1 ﬁx/s)

18 days–1 year

(10 mAh)

weeks (coin cell)

years (phone battery)

683 days

(coin cell, 235 mAh,

4 ﬁxes/h)

80 min

(19 mAh, 1 ﬁx/s)

–759 days

(200 mAh, 1 ﬁx/h)

Snapshot duration 5 chunks of 2 ms 2–20 ms 1–30 ms ?

Quantisation 2 × 2 bit ? 2 bit ?

Sampling frequency 16.368 MHz ? 16.368 MHz ?

Accuracy < 35 m

median < 9 m < 25 m

mean 15.5 m

Weight ? ? 1.3 g 11 g

Size [mm] 70 × 52 22 × 27 23 × 14 32 × 23 × 12

Available (2022) no yes

no no

Price N/A 189 USD N/A N/A

Open source no no no no

3Beuchert et al.

Journal of Open Hardware

DOI: 10.5334/joh.48

snapshots at multi-bit resolution. This improves the snapshot quality but also requires complex

and expensive hardware. For example, the ETHZ receiver records two-bit signals sampled at

16 MHz, which limits their microcontroller choice to one with a parallel input capture interface

(PARC) (Eichelberger et al. 2019). The CO-GPS receiver uses additional circuitry to convert its two-

bit GPS input stream at 16 MHz into a 16-bit parallel signal at 2 MHz, which a microcontroller

then captures using direct memory access (DMA) (Liu et al. 2012).

Moreover, the hardware is only part of a full snapshot GNSS solution. A complete system also

needs a signal processing chain to calculate positions from the raw snapshot data. However,

this software is not openly available for any of these systems, which renders users dependent

on the technology provider over the whole lifespan of their devices.

To address these issues, we developed SnapperGpS, a completely open-source, small, low-cost,

low-power snapshot GNSS system designed for tracking wildlife. The algorithmic details of the

SnapperGpS cloud-processing chain have already been described (Beuchert & Rogers 2021a).

This paper presents the accompanying hardware. The SnapperGpS printed circuit board (PCB)

measures 32.0 mm by 27.3 mm and weighs 3 g. The total weight, including an antenna

and a 40 mAh lithium-ion polymer battery, is 9 g. With such a battery, SnapperGpS can run

for more than a year. SnapperGpS works with short 12 ms snapshots sampled at only 4 MHz

with 1-bit amplitude quantisation. This unmatched low resolution allows us to use low-

cost, off-the-shelf components. The total component cost adds up to $21 for each device

if ordered in a batch of 100, excluding battery and antenna. SnapperGpS tags are used with

an open-source web application. The app serves as a tool for conﬁguring the tag and later

for uploading the recorded snapshots to the cloud for processing. We evaluated SnapperGpS

in controlled deployments, both moving and stationary. With good sky visibility, SnapperGpS

achieves a median error of 10 m. Modiﬁed versions of SnapperGpS have additionally been

deployed on free-ranging sea turtles and sea birds, demonstrating its usefulness for wildlife

tracking.

The rest of the paper is structured as follows: Section (1) Overview continues with the Overall

implementation and design of SnapperGpS. It includes sub-sections on the Electronics, the

Firmware and the Web application. Section (2) Quality Control covers how to safely operate

a SnapperGpS receiver and how to test that the system reliably provides accurate location

estimates over long periods of time. Examples of use cases are presented in (3) Application and

(4) Build Details provides the instructions to replicate SnapperGpS. Section (5) Discussion includes

a conclusion and an outlook on future work.

OVERALL IMPLEMENTATION AND DESIGN

SnapperGpS consists of three components: (i) a purpose-built energy-efﬁcient low-cost receiver,

(ii) a web application for conﬁguration of the receiver, and (iii) a cloud-based data processing

platform.

Electronics

We place all electronic components on a single side of a two-layered PCB to enable low-cost

assembly, as seen in Figure 1. The block diagram in Figure 2 shows all core components, which

we describe in the following.

The antenna captures GNSS signals in the GPS L1 band, which has a centre frequency of

1.57542 GHz. There are more GNSS signal bands, but the cheapest ICs work with the L1 band,

the oldest civilian band, and we can receive the modernised GPS L1C, the Galileo E1, the BeiDou

B1C, and the potential future GLONASS L1OCM signal in this band, too. This allows us to make

use of multiple satellite systems and, therefore, to increase localisation reliability by using more

satellites.

Sampling and storing satellite signals at a rate of multiple gigahertz is not possible with a low-

cost receiver. Therefore, we use the heterodyne method: by mixing the received signal with

an unmodulated signal from a local oscillator, we shift the original signal down to a lower, so-

called intermediate frequency.

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