Workshop on GNSS for Policy and Decision Makers
21st January 2022

Low-Cost and Smart-Phone Receiver Systems

Dinesh Manandhar, Associate Professor (Project)
Center for Spatial Information Science (CSIS), The University of Tokyo
dinesh@csis.u-tokyo.ac.jp2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 1

High-End Survey Grade Receivers
L5/E5/B2/L3

L2

L6/E6/B3

L1/E1/B1• Multi-frequency• GPS: L1/L2/L5• GLONASS : L1/L2/L3• GALILEO: E1/E5/E6• BDS: B1/B2/B3• QZSS: L1/L2/L5/L6• NAVIC: L5/S

• Multi-system• GPS, GLONASS, GALILEO, BeiDou, QZSS, NAVIC, SBAS etc• Price varies from $3,000 to $30,000 or more(including antenna)

2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 2

Low-Cost Receivers
L1/E1/B1*• Multi-System• GPS, GLONASS, GALILEO, BeiDou, QZSS, SBAS etc• Basically Single Frequency• L1/E1/B1-Band• Very soon: Multi-System, Multi Frequency, L1/L2 or L1/L5• Future trend for Mass Market System will be L1/L5• Some chip makers have already announced Multi-System, Multi-Frequency
GNSS Chips for Mass Market• Low Cost:• Less than $1,000• Our Target: $100 including everything. (L1 band only receiver)• But, currently about $300 including Antenna and all necessary Hardware, Software• This is using Dual-Band Receiver and Antenna• In future, dual band low-cost receivers based on L1/L2 and L1/L5 will be available

2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 3

Low-Cost High-Accuracy Receiver Systems
RTKDROID, MADROID, MAD-WIN, MAD-π

2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 4

Objectives• Develop Low-Cost High-Accuracy Positioning Systems (L-CHAPS)• System Integration of commercially available receiver or module• For RTK and MADOCA• Avoid use of computer to minimize the cost
• Use Single Board Computer (SBC)•• Use Tablet or Smart-Phone•$100 System PPK

RaspberryPi, Arduino, Spresense
PCAndroid devices are quite flexible and easier to use• Develop Easy to Use System in Field••••

A user without GNSS knowledge shall be able to use
Self-understanding interface
Suitable for remote operation and data logging
Operate with mobile power-banks• Promote GNSS and MADOCA Technologies Abroad through• Lectures, Trainings, Seminars, Workshops and Events• Joint Research and Joint Projects

We have no intention to prefer any brand names mentioned in these slides. They are used only for reference.

2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 5

Low-Cost High-Accuracy Receiver system
Development Cycle
DEC, 2016MAY, 2017

Low-Cost RTKMAR, 2018

Low-Cost MADOCA

Android Device
RTK / MADOCA / EWS / SAR
System2022

Enhancement ofMADOCA System
2021

What type of smart-phone
will emerge by 2025 ?

DEC, 20192022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 6

Type – A1: GNSS Receiver with Android Device

GNSS Antenna Rover

GNSS
ReceiverAndroidDevice
RTKDROID
Ver. : 1.0

RTCM forReal-time
RTK
WiFi

Type A1:
Rover Mode
Real-Time and Post-Processing RTK
Based on RTKLIB Engine
Real-time processing in Android Device
APP: RTKDroid
2022/02/02 8:23 PM

NTRIPCasterDinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

GNSS Receiver Module

Slide : 7

Screen Shots of RTKDROID and MADROID
Connect GNSS receiver toAndroid device(1) RTKDROID :For RTK or PPK(2) MADROID:
for MADOCA-PPP,
MADOCA-PPP/AR (future)2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 8

MADOCA System: Direct from QZSS or Online Correction Data
GNSS Receiver Only

QZSS

QZSS

GNSS Signals

GNSS Signals

GNSS Receiver + MADOCA Decoder

Antenna

AntennaGNSS /MADOCAReceiver

MADOCA PPP
Processor

Position
OutputGNSSReceiver

MADOCA PPP
Processor

Position
OutputOnline MADOCA
Correction Data

2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 9

Low-Cost MADOCA Receiver Systems: Product Types
MAD-WIN

MAD-π

MADROID

Platform / OS

Windows

RaspberryPi 3B or 4B

Android Device

GNSS ReceiverDefault : u-blox F9P
Other: Any dual-frequency ReceiverDefault : u-blox F9P only

Default : u-blox F9P
Other: Any dual-frequency Receiver

MADOCA Receiver

U-blox D9 only

U-blox D9 only

NA (MADOCA Online Correction Data only)

GNSS Receiver Data
FormatUBX, SBF, RTCM3UBX
SBF, RTCM3 (For online GNSS data)

UBX

MADOCA Correction Data
Format (Satellite)

UBX only

UBX only

NA

MADOCA Correction Data
Format (Online)

Online Services
from GPAS, UTokyo (Test Level)
UBX or RTCM3

Online Services
from GPAS, UTokyo (Test Level)
Online Services
UBX or RTCM3

GPAS Services,
RTCM3
UTokyo Online Service in the next release

System Architecture2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 10MADOCA PPP Receiver System

Use this baud-rate to receiver
GNSS Raw Data

Use this baud-rate to receiver
MADOCA Data

65Antenna
F9P GNSS Receiver
L1/L2/E5B

50

MADOCA Decoder
QZSS L6

COM Port: 1
GNSS DataCOM Port: 2
MADOCA Data

GNSS Antenna

2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 11

MAD-WIN / MAD-PI User Interface
ACB

MADOCA Correction
DataCases

GNSS Receiver

Case A

Connect Receiver
DirectlyConnect MADOCAReceiver DirectlyCase B

Connect Receiver
DirectlyGet MADOCA
correction data
through NTRIPConnect Receiverthough NTRIP

Get MADOCA
correction data
through NTRIPConnect Receiverthough NTRIPConnect MADOCA
Receiver Directly

Selection Settingin the Program

RX and DX

RX andOnline (MADOCA)

DCase C

Case D

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Online andOnline (MADOCA)

Online and DX

Slide : 12

MAD-WIN / MAD-PI User Interface

Log Files:
1. Solution: MADOCA PPP Solution in NEMA format
2. Rover: Rover RAW Data in receiver’s proprietary format
Can be used for PPK (Post-Processing Kinematic) Solution or
Post-Processing PPP
3. Correction: MADOCA PPP Correction Data in receiver’s
proprietary format
Can be used for Post-Processing MADOCA
2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 13

MAD-WIN Data Observation
Receiver: Online receiver access in Kashiwa / Correction Data: MADOCA Receiver in Bali
After three hours observation

After two hours observation

After few minutes observation

2022/02/02 8:23 PM

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 14

MAD-PI:MADOCA with RaspberryPi Device• MAD-Pi has been tested with RaspberryPi-3B device• It also works with RaspberryPi-4B• If the device does not work, please try with a different USB port

• Do not remove and insert SD Card several times. It may getdamaged.

• Observation data can be logged to an external USB memory
disk. Memory drive of upto 64GB is supported.
• Files are created at 6-hour interval with Date/Time based filename.

• Ras-Pi 4 device consumes more power than Ras-Pi 3 device.
Continuous operation of the device will generate heat. Keepthe device in well ventilated area• Do not keep the device in a closed box• We have set both Ras-Pi 3 and Ras-Pi 4 devices with touch
screens for easy operation.
• Mouse and External keyboard can be connected either via BT or USB ports• Ras-Pi device can be connected by an Android device using BT

2022/02/02 8:23 PM

Raspberry-Pi device with Touch Screen
Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 15

MADROID: MADOCA with Android Device

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 16

MADROID: MADOCA with Android DeviceDinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 17

GNSS Data from Android Device

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 18

GNSS Data from Android Smart-Phone• Android device can output GNSS only position data
• Since it uses multiple satellite systems and some device also uses L1 and L5 bands – Accuracy
is much better• Many Android devices with OS 7.0 or higher can output Raw Data
• These data are used for High-Accuracy data processing such as RTK• Some devices have Multi-Frequency (L1/L5) GNSS receiver• Multi-System (GPS, GLONASS, GALILEO, BEIDOU, QZSS, NavIC)• Multi-Frequency (L1/E1/B1, L5/E5)• Outputs more than 40 channels• Some devices output NAV BIT Data, AGC values and Antenna Phase Center• Google APIs are available to process GNSS raw data from a smart-phone

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 19

GNSS Raw Data Compatible Smart-Phones
Raw Data output used in System Score

S. No.

ModelSatellite Systems used in SystemScore

System Functio
Accumul
TotalL5Android Score n Score
NAV ated HW
Score AGC
Suppor GPS GLO GAL BDS QZSS SBAS
version Max: 6 Max: 5
MSG delta clock(D + E)
t(D)
(E)
range

43133

Xiaomi Mi 8
Samsung S8
Huawei P10

8.1
7
7

5
5
5

4
3
3

9
8
8

no
no
no

yes
yes
yes

yes
yes
yes

yes
yes
yes

yes
no
no

yes
yes
yes

yes
yes
yes

yes
yes
yes

yes
yes
yes

yes
yes
yes

nonono42

Huawei Mate 20 X

944

8

no

yes

yes

yes

yes

yes

yes

yes

no

yes

no

19
20
22
12Google Pixel 2 XL
Google Pixel 2
Samsung Note 8
Pixel 3 XL
Pixel 3

88
7.1
99

5
54
4
4223
3
3

7
7
7
7
7

yes
yes
no
yes
yes

no
no
yes
no
no

no
no
yes
yes
yes

yes
yes
yes
yes
yes

no
no
no
no
no

yes
yes
yes
yes
yes

yes
yes
yes
yes
yes

yes
yes
yes
yes
yes

yes
yes
yes
yes
yes

yes
yes
no
no
no

no
no
no
no
no43

Huawei Mate 20 RS

94

3

7

no

no

yes

yes

yes

yes

yes

yes

yes

no

no44

Huawei Mate 20 Pro

94

3

7

nono

yes

yes

yes

yes

yes

yes

yes

nono45
10Huawei Mate 20
Huawei P20

98.1

433
3

76

no
no

no
yes

yes
yes

yes
yes

yes
no

yes
yes

yes
yes

yes
no

yes
no

no
yes

no
no

11

Samsung Galaxy S98

3

3

6no

yes

yes

yes

no

yes

yes

no

no

yes

no

18

Huawei Mate 10 Pro

83

3

6

no

yes

yes

yes

no

yes

yes

no

no

yes

no

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp
Check  https://developer.android.com/guide/topics/sensors/gnss
for Latest Updates

Slide : 20

Android Raw Data Logging Tool – 1: GnssLogger

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 21

GNSS Raw Data Analysis Tool for GnssLogger• GNSS Analysis APP• Matlab-based Tool
• Linux, Windows, MacOS• Version 2.6.3.0• Release Notes:
https://developer.android.com/guide/topics/sensors/g
nss#releaseGNSS Analysis app v2.6.3.0 release notes.

Click for KML FileClick for Report File

The GNSS Analysis app is built on MATLAB, but you don't need to have MATLAB to run
it. The app is compiled into an executable that installs a copy of the MATLAB Runtime.

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 22

Position Output from Android GNSS Receiver, Tokyo University, Komaba Campus• Standard Position Computation• No DGPS or RTK Corrections• All visible GNSS Satellites are used
• Frequency : L1/L5/E5• Surrounding : Tall Buildings aroundDinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 23

Output from GNSS Analysis Tool, Data Logged by GNSSLogger
Location:
Kennedy Space Center
FloridaData logged by Mi8 Smart-phone inside the car
Driving from Hotel to Kennedy Space Center

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 24

Output from GNSS Analysis Tool, Data Logged by GNSSLogger

Kennedy Space Center

Data logged by Mi8 Smart-phone inside the car
Driving from Hotel to Kennedy Space Center
Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 25

Xiaomi Mi11 Lite 5G Screen Shots

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 26

Xiaomi Mi11 Lite 5G Screen Shots

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 27

Sample GNSS Raw Data from Mi11 Lite 5G
Sample GNSS raw data can be downloaded from the following website:
https://home.csis.u-tokyo.ac.jp/~dinesh/GNSS_Train.htm
Data were taken at the same time by using 4 or 5 different types of devices.
This will help to compare accuracy from different devices as well.

Smart-Phone Data
Xiaomi Mi8 (a)Xiaomi Mi8 (b)Xiaomi Mi8 (c)Xiaomi Mi11 Lite 5G

OppoReno 3ADay 1

Data 01

Data 02

Data 03

Data 08
Data 09

Data 10

Day 2

Data 04

Data 05Data 06

Data 07

GNSS Raw Data from android devices open new opportunities to develop location based applications
with high accuracy that were not possible before.

Dinesh Manandhar, CSIS, The University of Tokyo, dinesh@csis.u-tokyo.ac.jp

Slide : 28