Performance of KSP Real-time VLBI Correlation Processing Software (RKATS)

Mamoru Sekido1(sekido(AT), Tetsuro Kondo1, Hitoshi Kiuchi2, Hiroto Sato3, Yasuhiro Koyama1, and Tetsuo Masubuchi4

1 Kashima Space Research Center
Communications Research Laboratory
893-1 Hirai, Kashima, Ibaraki 314-0012, Japan

2Communications Research Laboratory
4-2-1 Nukui-kita, Koganei, Tokyo 184-8795, Japan

3Kety Co.Ltd.

4CosmoResearch Co. Ltd.

1. Introduction

Key Stone Project(KSP) real-time VLBI observations started in June of 1997 by using Asynchronous data Transfer Mode(ATM) network. Real-time VLBI correlation processing software "RKATS" has developed for fully automatic real-time VLBI data processing. Overview of RKATS was reviewed in TDC News No.9 p.15. In this report, "Dynamic Clock Adjustment" and "Automatic Fringe Search" functions are introduced as key functions for RKATS.

2. Differences between Tape-based VLBI and Real-time VLBI

The main differences of correlation processing between tape-based VLBI and real-time VLBI are listed in Table 1.

Table 1. Differences between tape-base VLBI and real-time VLBI.
Data transportation
and replay
Human operation is inevitable at work of Magnetic tape transportation and tape mount on recorders Real-time data transfer by ATM enables automatic operation.
Log information Observation information and Clock parameter is provided by log file. Information is collected by computer network just before the observation.
Trouble recovery Trouble at data processing can be recovered by re-processing of recorded data. Stop of data processing due to troubles leads to data loss directly.
Rapidity of output Analysis result comes out 1-2 days after observation. Analysis result comes out just 10-20 minutes after observation.

Real-time VLBI is advanced from the standpoint of automatic operation and rapidity of output, but interruption of correlation processing due to any problems leads to direct loss of data. Therefore, non-stop operability is strongly requested of real-time correlation processing software.

Except for hardware errors and software hang ups, most probable cause of data loss would be wrong clock parameters. Wrong clock parameters will move fringes out of the lag window of the correlator, and such data cannot be used for baseline analysis. Also, fringe monitoring and adjustment of clock parameters by an operator is difficult, because VLBI experiments may start at midnight and the operators are not supposed to be familiar with VLBI. Therefore we implemented "Dynamic Clock Adjustment(DCA)" and "Automatic Fringe Search(AFS)" functions in RKATS. By using these functions, fully automatic real-time daily VLBI observation has realized.

3. Automatic Fringe Search and Dynamic Clock Adjustment

Figure 1. Performance test of AFS(left) and DCA(right) function. Clock parameter of Kashima is fixed as reference. For the performance test, clock parameters of Koganei, Miura, and Tateyama are artificially biased by 10 usec, -10 usec, and -5 usec respectively. At first, correlation has started in "Normal Mode" but fringes were not detected. Then RKATS changed the mode to "Fringe Search Mode" and detected fringes automatically. After that clock parameter was adjusted, the mode was returned back to "Normal Mode". In the "Normal Mode" operation, DCA function adjusts the clock parameter and keeps the fringes at the center of lag window.

Figure 1 shows the clock parameters are adjusted by AFS and they are kept almost within +/-0.1 usec by DCA function. AFS and DCA works as follows:

Even though the clock offset is changed by about a few hundred nanoseconds, no differences in the analysis results were observed.

Data processed in "Fringe Search Mode (FSM)" is unusable for baseline analysis. The frequency of transition to FSM must be as small as possible. For stabilization of AFS and DCA, RKATS has several parameters. They are listed in Table 2.

By optimizing these parameters empirically, RKATS can be tuned to operate as reliably as possible.

Table 2. Parameter for AFS and DCA.
Parameter nameMeanings
Fringe Search Mode transition threshold If ratio of fringe detection (#detected/#total) become lower than this value, correlation mode is changed to FSM.
Averaging Number Averaging number for fringe detection ratio.
SNR threshold SNR threshold to judge fringe detection.
Source list for DCA radio source list, on which fringe is expected to be detected certainly.

4. Summary

AFS and DCA are introduced as key functions of RKATS. Under the combination of RKATS and automated KSP system, baseline vectors among four stations are being measured automatically daily.

Updated on November 20, 1997. Return to CONTENTS