1. Prototype LRPT Receiver
NOAA Satellite Direct Readout Conference for the Americas
December 9-13, 2002
Miami, FL
Wai Fong
NASA/GSFC
Code 567
Microwave and Communications System Branch

2. Background
Low-Resolution Picture Transmission (LRPT) is a proposed standard for direct broadcast transmission of satellite weather images for METOP
LRPT definition is a joint effort by EUMETSAT and NOAA
Goddard Space Flight Center was tasked to build an LRPT Demonstration System (LDS) and study the protocol performance

3. Objective
To develop and demonstrate the feasibility of a low-cost receiver utilizing as much Commercial-off-the-shelf (COTS) equipment as possible.
Determine the performance of the protocol in a simulated Radio Frequency (RF) environment.

4. Approach
Utilize Personal Computers as the primary processing component.
Develop all software elements to process and control data flow.
Identify and procure COTS RF modulator/demodulator (MODEM).
Utilize the Institute for Telecommunications Sciences (ITS) study for modeling two noise environments: Residential (Lakewood, CO) and Business (Downtown Denver, CO).
Perform BER analysis of protocol and simulate a satellite pass.
Use Modulated Lapped Transform (MLT) instead of current JPEG variant.

5. Top-level Diagram

6. Transmitter Description
Compress, channel code and CCSDS format AVHRR data off-line and store in the Transmitter buffer
RF Modem performs QPSK modulation

7. Transmitter Block Diagram

8. Key Features of the Receiver
Hardware elements:
Modem performs QPSK demodulation
Bit synchronization producing 3-bit soft-decision samples
Real-time Software elements:
Unique Word (UW) synchronization
Convolutional de-interleaving
Viterbi decoding
CCSDS Frame Synchronization
CCSDS Block de-interleaving
Reed-Solomon decoding
CCSDS Virtual-Channel processing
CCSDS Packet processing
Modulated Lapped Transform (MLT) decompression
Image Display
Status/Statistical analysis and display

9. Receiver Block Diagram

10. Noise and Scintillation Generation
Noise and Scintillation patterns are generated by ITS models.
Use Pattern Generators to drive programmable attenuators and phase shifters.

11. Testing Block Diagram

12. Summary of Results
40% of the CPU bandwidth required for Receiver processing.
7 dB of coding gain at the output of the Viterbi 10-4 BER in a residential environment with Man-made/Gaussian noise and Scintillation.
Coding gain decrease to 5.2 dB as the Man-made noise increased for the urban environment.
Use of convolutional interleaving can provide as much as 2 dB of gain.
The output of the R-S decoder was virtually error-free as long as the receiver maintained solid lock.
For residential (low noise) environments e.g. Lakewood, nearly 100% coverage for either Yagi or Omni antenna.
In high noise urban environments like Downtown Denver, 65% coverage using an Omni antenna.

13. Conclusion Protocol mitigates scintillation and man-noise effects.
In larger more populated metropolitan areas, use a tracking Yagi antenna and/or a better receiver due to the noisier environment.
Inexpensive LRPT receivers can be made by using software to perform most of the receiving functions.

14. Demonstration
Pass simulation of Downtown Denver with Omni Antenna in Man-made noise/Gaussian noise and Scintillation
Pass simulation of Lakewood with Yagi Antenna in Man-made noise/Gaussian noise and Scintillation