software, statistical analyses of meteor activities is based on the results obtained at many Ham-band. Radio meteor Observation (HRO) sites throughout the ...
Development of an automatic echo-counting program for HROFFT spectrograms Kazuya Noguchi and Masa-yuki Yamamoto (Kochi University of Technology) Abstract. Radio meteor observations by Ham-band beacon or FM radio broadcasts using “HROFFT” (Ham-band Radio meteor Observation Fast Fourier Transform) an automatic operating software have been performed widely in recent days. Previously, counting of meteor echoes on the spectrograms of radio meteor observation was performed manually by observers. In the present paper, we introduce an automatic meteor echo counting software application. Although output images of the HROFFT contain both the features of meteor echoes and those of various types of noises, a newly developed image processing technique has been applied, resulting in software that enables a useful auto-counting tool. There exists a slight error in the processing on spectrograms when the observation site is affected by many disturbing noises. Nevertheless, comparison between software and manual counting revealed an agreement of almost 90%. Therefore, we can easily obtain a dataset of detection time, duration time, signal strength, and Doppler shift of each meteor echo from the HROFFT spectrograms. Using this software, statistical analyses of meteor activities is based on the results obtained at many Ham-band Radio meteor Observation (HRO) sites throughout the world, resulting in a very useful “standard” for monitoring meteor stream activities in real time.
1. Introduction Ham-band Radio meteor Observation (HRO) has been developed as VHF-band (30 MHz-300 MHz) forward-scattering radar since 1996 (Maegawa, 1999). Recently, HRO has become one of the “standard” radio meteor observations and is widely performed by amateur meteor observers, as well as amateur radio communicators, all over the world. The observation of HRO is usually performed by a two-element antenna, a receiver, and a PC with a sound card. A beacon wave of 53.75 MHz is commonly used for HRO in Japan. The observation software “HROFFT” (Ham-band Radio meteor Observation) Fast Fourier Transform (developed by Kazuhiko Ohkawa) performs FFT processing each second to create a dynamic spectrum image every 10 minutes, as shown in Figure 1. Powerful and useful software such as HROFFT enables amateur observers to build a simple automatic radio observatory for monitoring meteor activities. Recently, as an application of HRO, the HRO interferometer was developed by three teams in Japan (Ohkawa, 2006; Maegawa et al., 2006; Yamamoto et al., 2007), and the HRO interferometer has operating since 2005 at Kochi University of Technology. Since the HROFFT observation software creates a PNG image for every 10-minute period, it produces 144 images per day and 4,320 images in one month. In the present case, a six-channel HRO system has been continuously operated since 2003 at Kochi University of Technology using a two-channel version of HROFFT. This version produces 4,320 × 3 = 12,960 sheets per month, and several meteor echoes are usually found on each HROFFT spectrogram, so that the observers have to analyze the enormous number of images in order to obtain the meteor activities. Meteor echoes are easily found on the HROFFT spectrograms and are usually counted manually by
HRO observers. Therefore, in order to analyze meteor activities from HRO data sets, the energy and time demanded of observers are significant. As a result, many HROFFT image archives are simply stored on a PC without being analyzed. In addition, manual echo-counting by individual observers with different counting criteria causes another problem in obtaining “standards” with respect to meteor activities. Ogawa et al., (2003) reported approaches for obtaining a “standard” based on global HRO observation data archives by being averaged for local dependences. More efforts in developing hardware and software were called in order to calibrate the absolute sensitivity of receiver and/or the parameter of software at each site because the sensitivity and noise level are different at each site and affected by local environment. Therefore, the present paper proposes an automatic counting program in which an image processing technique is applied. The proposed program can provide a “standard” method of automatic counting for HRO spectrograms in order to obtain more useful outputs from global HRO data.
Figure 1. Example image of a two-channel HROFFT spectrogram. The horizontal axis indicates the local time [s]. The vertical axis of the spectrogram indicates the frequency [kHz], and vertical axis of the intensity graph indicates the relative power [dB]. Ten-minute observations are recorded in the spectrogram image as 14-step colored dynamic spectra, and intensity graphs for each channel are added below. The beacon wave signal reflected by meteors is detected by receivers and down-converted into the audible frequency of approximately 900 Hz in the case of the usual HRO. Signals stronger than 10 dB in intensity are shown in yellow in the intensity graph, where 0 dB is set near the lowest noise level at each site.
2. Development of “Meteor Echo Counter” software Meteor observation by forward-scattering radar is deeply affected by the geometrical configuration because the reflection region by each meteor trail should be a ”mirror” for electromagnetic waves in three-dimensional space between transmitter and receiver. The configuration changes along the motion of radiant point for each meteor swarm. Especially in the case of zenith passage of the radiant point, the meteor echoes might be vanished because the reflection planes (mirrors) are created almost vertically with respect to the horizon. However, statistical analyses of meteor activities based on the results from several HRO observation sites around the world provides a very useful “standard” for monitoring meteor stream activities in real time. The software “Meteor Echo Counter” could provide an evolutional technique to speed up statistical processing. The development of “Meteor Echo Counter” software is described below. The HROFFT spectrograms contain not only real meteor echoes but also noises of various types. These noises are categorized into, for example, vertical line noises by lightning discharges, horizontal line noises by artificial sources (such as interference by electronic power supplies or home electric appliances), airplane echoes, and ionospheric noises, as shown in Figure 2. Therefore, applying the image-processing technique, the software is designed not only to count meteor echoes accurately and automatically but also to eliminate these types of noises. For example, when heavy ionospheric noises are received, as is shown in Figure 2, the software will automatically skip counting meteor echoes on the exact image. Although vertical and horizontal line noises are easy to eliminate, airplane echoes are difficult to eliminate because of their complicated structures.
Figure 2. Examples of various types of noises. As a basic method by which to distinguish the above-mentioned typical meteor echoes, the program first performs the image binarization process to generate black and white images. Thereafter, the program begins to search each meteor echo in the following searching algorithm. The binarized echo images searched from left to right or up and down from any white points, as shown in Figure 3, where the search range is represented by gray. If the search process can identify another white point, these two white points will be recognized as an independent echo combination, followed by a second search process starting from the adjacent white point. Through this procedure, the search range was
designed as a vertically elongated diamond based on the characteristics of meteor echoes with a Doppler shift that varies with content, depending on the traveling speed of the meteor trail (scattering region) toward the observation site. Clear and precise counting of meteor echoes was established by applying this well-considered and tested method.
Figure 3. Schematic diagram of the echo search procedure and its search range.
3. Results The software automatically produces “processed result” images, as shown in Figure 4. In the figure, distinguished from the various noises, each area surrounded by gray is treated as one echo. The red line indicates the portion of line type noises after their discriminations. When a long meteor echo (usually defined as 10 seconds or longer) is detected, the duration time of the echo is automatically calculated and displayed on the image at the upper left of each long echo, where the unit of time is seconds. The long echo on Figure 4 was observed for 18 seconds, for example. The “echo-counting information result” and “meteor information result” are generated automatically (See Tables 1 and 2). The number of meteor echoes and the number of long echoes per channel are written into the text files of the “echo-counting information result”. The software also outputs the detection time, the center frequency, the duration time, and the maximum signal strength on the dynamic spectrum for each meteor echo in the text files of the “meteor information result”. In addition, the software can automatically generate activity graphs of meteor echoes every hour. Users can confirm the progress of the auto-counting process by watching these graphs in quasi real time. The number of meteor echoes usually depends on the observation environment, i.e., the noise environment of the receiving station (Rx), the intensity of the transmitting beacon waves at the transmitting station (Tx), and the distance between the Tx and Rx stations. In the echo-counting process, there are some threshold parameters to be used according to the environments of their receivers. In this software, users can change these parameters from GUI windows on demand.
Figure 4. Example of a processed result image. This image corresponds to the spectrogram of Figure 1.
Table 1.
Example output of “echo-counting information result”. For Channels 1 and 2, “echo”
indicates the number of meteor echoes, “long” indicates the number of long-lasting meteor echoes, “hikou” indicates the number of airplane echoes, “all” indicates the total white pixels after the binarization process, “noip” indicates the flag of an extremely noisy spectrogram (the value will be 1 if the software skips counting because the threshold has been exceeded), and “Yhei” indicates the averaged position of observing frequency.
Table 2.
Example output of “meteor information result”. Luminance varies from 0 to 13 (14 steps).
4. Performance assessment In order to obtain a performance assessment of the software, we compared 10-day counting data between manual counting and automatic software counting, in detail. The results for the cases of observation sites with few noises and several noises are shown in Figures 5 and 6, respectively. In both figures, the red line indicates the manual counting results and the blue line indicates the automatic counting results. The green and orange bars represent the number of average echoes longer than 10 seconds. Note that the observation sites of both figures are geographically different from each other. The former is 340 km distant from the Tx site, whereas the latter is 200 km distant from the Tx site. The observation site of Figure 5 is located in a rural area, whereas the observation site of Figure 6 is located in an urban area near an international airport with heavy traffic. Therefore, the latter is much noisier, as noise from approximately five airplanes is identified on each HROFFT spectrogram. As a result, assuming an error range of less than two echoes between the automatic counting and the manual counting for a single image, the rate of agreement becomes 99 % for the rural observation site and 81 % for the urban one, respectively, as is shown in Figures 5 and 6. A clear meteor activity profile, which is thought to be caused by the Geminids, was successfully identified by the automatic echo-counting software.
Figure 5.
Case in which the observation site is affected by few noises. “HR” denotes Hourly Rate
(meteor echoes observed in one hour), and “MEC” denotes Meteor Echo Counter (name of this software).
Figure 6. Case in which the observation site is affected by several artificial noises.
5. Discussion Although some errors remain in the processes of auto-echo-counting on HROFFT spectrograms when the observation site is affected by numerous noises, an average coincidence of almost 90 % was realized. The developed software “Meteor Echo Counter ver.1.0” has the capability of monitoring meteor activities even in observing an environment with several artificial noises and/or airplane echoes. Using a PC having a 2.4-GHz Pentium4 CPU with 496 MB of RAM (approximately 450 Mflops per second), the processing time of the auto-echo-counting process on the successive HROFFT data for one month was approximately five hours. By applying the software to the HROFFT spectrogram data of Kochi University of Technology that has been archived for more than two years, meteor activity graphs were automatically produced with clear peaks near the timings of encounters of annual meteor storms of Quadrantids, η-Aquarids, Perseids, Orionids, and Geminids. In the above-mentioned PC environment, the processing time of the analyses for two-year data was approximately 120 hours. The software is able to perform automatic echo-counting, creating detailed meteor echo information without a placing a significant workload on observers.
6. Conclusion The software “Meteor Echo Counter ver.1.0” was developed as an automatic echo-counting program specified for the HROFFT spectrograms, providing the first “standard” software for automatic HRO echo counting for amateur observers. This software will help HRO observers to obtain scientific outputs from their HRO observations. The software is currently available on the Web (Noguchi, 2007). Japanese and English versions of this software have already been released. Based on feedback from numerous HRO observers, this software will be distributed and used in global. Moreover, in combination with network software, Meteor Echo Counter ver.1.0 could produce a quasi-real-time meteor alert system for occasional meteor swarm activities in the near future.
Acknowledgments The authors would like to thank Mr. Masayoshi Ueda (The Nippon Meteor Society) for kindly providing his observation data and manual counting results for comparison. All users’ feedbacks for improving the software algorithm are gratefully acknowledged.
References Maegawa, K., HRO: A new forward-scatter observation method using Ham-band beacon, WGN, 27, 64-72, 1999. Maegawa, K., Uno, S., Horiuchi, H., Okamoto, G, and Yamamoto, M.-Y., Development of Radio Interferometer System for Meteor Observation, Research reports of Fukui National College of Technology, Natural science and engineering, 39, 31-36, in Japanese with English abstract, 2006. Noguchi, K., “Meteor Echo Counter” on web, http://www.gs.kochi-tech.ac.jp/115073w/ , 2007. Ogawa, H., Toyomasu, S., Ohnishi, K., Amikura, S., Asahina, T., Miyao, K., and Maegawa, K., Leonids 2001 by radio meteor observation all over the world, ISAS rep. SP., 15, 81-88, 2003. Ohkawa, K., Meteor observation by interferometer, Radio Meteor Observation Meeting 2006, Hachioji, Tokyo, in Japanese, 2006. Yamamoto, M.-Y., Horiuchi, H., Okamoto, G., Hamaguchi, H., and Noguchi, K., Development of HRO interferometer at Kochi University of Technology, Proc. of Intl. Meteor Conf. 2006, 2007.
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