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A method for processing ionograms based on correlation technique
Phys. Chem. Earth (C), Vol. 26, No. 5, pp. 367-371, 2001
Pergamon
© 2001 Elsevier Science Ltd. All fights reserved 1464-1917/01/$ - see front matter
PII: S1464-1917(01)00015-0
A Method for Processing lonograms Based on Correlation Technique C. Seotto Istituto Nazionale di Geofisica, Via di Vigna Murata 605, 00143 Roma, Italy Received 5 dune 2000; accepted 31 October 2000
Abstract. The application of correlation teelmique for automatic scaling of ionograms is presented. A method of automatic scaling of critical frequency foF2 and MUF(3000) is shown. The ionograms are considered as digital images and the detection process of the traces is performed without using information on polarization. For this reason the method can be applied to ionogram recorded by single antenna systems. © 2001 Elsevier Science Ltd. All fights reserved
1 Introduction The importance of real time ionosphel"ic data in recent years has increased the interest in automatic scaling of ionograms and some software has been produced (Fox and Blundell, 1989; Tripathi, 1998; Tsai et al., 1998). The most performing software programme is the ARTIST system (Reinisch and Huang, 1983), developed at the University of Lowell, Centre for Atmospheric Research (UMLCAR). In this system the separation between the two different polarized components of the reflected radio wave is performed by the receiving system, that is equipped by crossed antenna. The objective of this work is to show the results obtained in automatic scaling using an algorithm based on the recognition by correlation method of the typical structure of the ionogram trace. By using this technique the ionogram can be considered as an image and the separation of the ordinary and extraordinary traces is performed as a part of the recognition procedure. As a consequence it can be applied to both, single antenna system and crossed antenna system ionoglams.
2 Description of the procedure We are interested in showing the good performance of correlation technique for the automatic scaling of Correspondence to: C. Scotto
ionograms, even if it is applied to low quality ionograms. For these reasons we considered the ionogram reported in Fig. 1. It has been acquired by a digisondc DPS 42 developed at UMLCAR and we reduced the quality of image adding random noise. Information about polarization has not been considered. Figure 2 is a resized image used for further processing. A resizing is required because for performing correlation it is necessary to have both the images on the same scale. Here the resized image has a resolution of 0.1 MHz/pixel on x axis and 10 km/pixel ony axis One can observe the decrease in the quality with respect to Fig. 1. The ordinary and the extraordinary components of the ionogram trace are detected by comparing (in term of correlation) suitable standard images ofF2 traces with the ionogram to be scaled. In this work these suitable standard traces have been selected on a base of data constituted of 120 digital ionograms recorded at the ionospheric station of Rome for different times, seasons, and solar activity. Each standard F2 trace is moved to different positions over the ionogram to be scaled. For each position the correlation is performed between the standard image of F2 trace and the part of the ionogram in which it is placed. In this way a matrix of correlation indices is obtained for every standard F2 trace. At this stage the position of the maximum of correlation is memorized for the particular standard F2 trace. This procedure is repeated for each standard trace considered (in this case 4) and we obtained the position of 4 maximums. The results of these processes for each of the traces considered are shown in Fig. 3a,b,c,d. The matrices of correlation are reported in color levels. The positions of the maximums and the respective positions of the sample trace arc also indicated. At the end, the maximum of correlation between the 4 maximums calculated, is assumed as the position of the ionogram trace (Fig. 3e). Using the procedure above the most evident trace (we will call it A) is detected. A problem is constituted by the typical double trace of the ionogram that must be separated. In this algorithm the trace A is temporarily
368
C. Scotto: A Method for Processing lonograms
deleted and the same procedure is repeated (Fig. 4a,b,c,d,e). In this way the other trace (the less evident, we will call it B) is detected. As a final step the identification of ordinary and extraordinary trace between A and B is performed by the position.
comparison with several typical shapes of F2 trace The correlation matrix and the position of the traces roughly detected are shown in color levels in fig. 7.
Observing Fig(s). 3e and 4e it is evident that the detection process can only give the approximate location of the ionogram traces. Although this information is not complete, it is very important in our analysis procedure. Starting from the approximate positions the real points are assumed selecting the points in which the signal has the maximum intensity. This selection is performed in a fixed size neighbourhood, A minimum threshold can also be fixed. Fig. 5 reports the result of this procedure. In this figure gray points are the approximate positions of the traces detected and the red and blue are the points acquired for ordinary and extraordinary traces respectively.
The correlation method shows good performance in the detection of the ionogram trace. This method can be applied to ionograms from monitoring ionosonde equipped by single antenna apparatus. As a further development this method can be studied to attempt the automatic scaling of all the characteristics of the ionogrants. In this case we will have the problem of an increase in time calculation that can be overlapped by applying the same technique to a limited portion of the ionogram. This is possible because the F1 and E layers have a more regular behavior than F2 layer (Davies, 1989).
3 Conclusions
References.
Using the acquired points the traces are built up by minimum square method. This method is applied among a particular family of functions whose shape is the typical shape of the ionogram. The vertical asymptote of the analytical function found by minimum square method corresponds to the critical frequency foF2. The MUF is calculated using the same function numerically applying the tangent transmission curve method. The analytical functions and the tangent transmission curve are plotted in Fig. 6. In detail it can be noted that the procedure of cross correlation of the suitable F2 traces (Fig(s). 3a,b,c,d and Fig(s). 4a,b,c,d) has been applied to a selected portion of the ionogram. This portion has been selected by a similar preliminary process that permits a strong reduction in time calculation. The reduction in time calculation is useful because it permits the introduction of the
Davies, K., lonospherwRa&o, Peter Peregrinus Ltd.,1989 Reinisch, B. W., and X. Huang , "Automatic calculation of electron density profiles from digital ionograms 3. Processing of bottomside ieftogranm", Radio Science, 18, 477-492, 1983. Fox, M W., and C. Blundell, "Automatic sealing of digital ionograms", Radio Science, 24, 747-761, 1989. Tripnthi ,Y., "Autoseale software eomputerized processing fi'om years of hourly data comparison", Proceedings of Session G5 at the XXVth Cnmeral Assembly of the International Union of Radio Science (URSI), Lille, France, August 28 - September 5, 22-29, 1996. Tsai, L. C., F. T B~key,. and J. Y. Liu "Automatic ionogram trace identification using fuzzy classification toahniques", Proeo~iing~ of Session G5 at the XXVth General Assembly of the International Union of Radio Science (URSI), Lille, France, August 28 - September 5, 4550,1996.
C. Scotto: A Method for Processing lonograms
rI
,,,
•
Fig. 1 The ionogram used for the automatic scaling. This ionogram has been acquired by a DPS 42. The quality of the image has been artificially decreased by adding random noise. The information about polarization has not been considered.
..i
Fig. 2 The ionogram after the resizing procedure introduced to perform the comparison Coy correlation method) with the typical shapes of F2 traces.
369
370
C. Scotto: A Method for Processing lonograms
Fig. 3 The matrices of correlation found for each of the standard traces considerecL For each case the position of the trace has been assumed where the correlation is maximum (a,b,c,d). At the end the absolute maximum has been considered (e). For the first time this procedure has been applied for the detection of the most evident trace.
Fig. 4 The same as figure 3, with reference to the detection of the less evident trace
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.f
C. Scotto:A Methodfor ProcessingIonograms
371
0
Fig. 5 The points used to build up the analytical limctions that approximate the ionogram traces. In red the points for ordinary trace, in blue for extraordinary trace.
° .
. •
i
.... ~id4~ :2~" Fig. 6 The analytical functions found for the F2 traces by minimum square method. Tangent transmission curve is also indicated.
Fig. 7 The matrix of correlation found for the preliminary detection of the ionogram traces and the approximate position found.
Pergamon
© 2001 Elsevier Science Ltd. All fights reserved 1464-1917/01/$ - see front matter
PII: S1464-1917(01)00015-0
A Method for Processing lonograms Based on Correlation Technique C. Seotto Istituto Nazionale di Geofisica, Via di Vigna Murata 605, 00143 Roma, Italy Received 5 dune 2000; accepted 31 October 2000
Abstract. The application of correlation teelmique for automatic scaling of ionograms is presented. A method of automatic scaling of critical frequency foF2 and MUF(3000) is shown. The ionograms are considered as digital images and the detection process of the traces is performed without using information on polarization. For this reason the method can be applied to ionogram recorded by single antenna systems. © 2001 Elsevier Science Ltd. All fights reserved
1 Introduction The importance of real time ionosphel"ic data in recent years has increased the interest in automatic scaling of ionograms and some software has been produced (Fox and Blundell, 1989; Tripathi, 1998; Tsai et al., 1998). The most performing software programme is the ARTIST system (Reinisch and Huang, 1983), developed at the University of Lowell, Centre for Atmospheric Research (UMLCAR). In this system the separation between the two different polarized components of the reflected radio wave is performed by the receiving system, that is equipped by crossed antenna. The objective of this work is to show the results obtained in automatic scaling using an algorithm based on the recognition by correlation method of the typical structure of the ionogram trace. By using this technique the ionogram can be considered as an image and the separation of the ordinary and extraordinary traces is performed as a part of the recognition procedure. As a consequence it can be applied to both, single antenna system and crossed antenna system ionoglams.
2 Description of the procedure We are interested in showing the good performance of correlation technique for the automatic scaling of Correspondence to: C. Scotto
ionograms, even if it is applied to low quality ionograms. For these reasons we considered the ionogram reported in Fig. 1. It has been acquired by a digisondc DPS 42 developed at UMLCAR and we reduced the quality of image adding random noise. Information about polarization has not been considered. Figure 2 is a resized image used for further processing. A resizing is required because for performing correlation it is necessary to have both the images on the same scale. Here the resized image has a resolution of 0.1 MHz/pixel on x axis and 10 km/pixel ony axis One can observe the decrease in the quality with respect to Fig. 1. The ordinary and the extraordinary components of the ionogram trace are detected by comparing (in term of correlation) suitable standard images ofF2 traces with the ionogram to be scaled. In this work these suitable standard traces have been selected on a base of data constituted of 120 digital ionograms recorded at the ionospheric station of Rome for different times, seasons, and solar activity. Each standard F2 trace is moved to different positions over the ionogram to be scaled. For each position the correlation is performed between the standard image of F2 trace and the part of the ionogram in which it is placed. In this way a matrix of correlation indices is obtained for every standard F2 trace. At this stage the position of the maximum of correlation is memorized for the particular standard F2 trace. This procedure is repeated for each standard trace considered (in this case 4) and we obtained the position of 4 maximums. The results of these processes for each of the traces considered are shown in Fig. 3a,b,c,d. The matrices of correlation are reported in color levels. The positions of the maximums and the respective positions of the sample trace arc also indicated. At the end, the maximum of correlation between the 4 maximums calculated, is assumed as the position of the ionogram trace (Fig. 3e). Using the procedure above the most evident trace (we will call it A) is detected. A problem is constituted by the typical double trace of the ionogram that must be separated. In this algorithm the trace A is temporarily
368
C. Scotto: A Method for Processing lonograms
deleted and the same procedure is repeated (Fig. 4a,b,c,d,e). In this way the other trace (the less evident, we will call it B) is detected. As a final step the identification of ordinary and extraordinary trace between A and B is performed by the position.
comparison with several typical shapes of F2 trace The correlation matrix and the position of the traces roughly detected are shown in color levels in fig. 7.
Observing Fig(s). 3e and 4e it is evident that the detection process can only give the approximate location of the ionogram traces. Although this information is not complete, it is very important in our analysis procedure. Starting from the approximate positions the real points are assumed selecting the points in which the signal has the maximum intensity. This selection is performed in a fixed size neighbourhood, A minimum threshold can also be fixed. Fig. 5 reports the result of this procedure. In this figure gray points are the approximate positions of the traces detected and the red and blue are the points acquired for ordinary and extraordinary traces respectively.
The correlation method shows good performance in the detection of the ionogram trace. This method can be applied to ionograms from monitoring ionosonde equipped by single antenna apparatus. As a further development this method can be studied to attempt the automatic scaling of all the characteristics of the ionogrants. In this case we will have the problem of an increase in time calculation that can be overlapped by applying the same technique to a limited portion of the ionogram. This is possible because the F1 and E layers have a more regular behavior than F2 layer (Davies, 1989).
3 Conclusions
References.
Using the acquired points the traces are built up by minimum square method. This method is applied among a particular family of functions whose shape is the typical shape of the ionogram. The vertical asymptote of the analytical function found by minimum square method corresponds to the critical frequency foF2. The MUF is calculated using the same function numerically applying the tangent transmission curve method. The analytical functions and the tangent transmission curve are plotted in Fig. 6. In detail it can be noted that the procedure of cross correlation of the suitable F2 traces (Fig(s). 3a,b,c,d and Fig(s). 4a,b,c,d) has been applied to a selected portion of the ionogram. This portion has been selected by a similar preliminary process that permits a strong reduction in time calculation. The reduction in time calculation is useful because it permits the introduction of the
Davies, K., lonospherwRa&o, Peter Peregrinus Ltd.,1989 Reinisch, B. W., and X. Huang , "Automatic calculation of electron density profiles from digital ionograms 3. Processing of bottomside ieftogranm", Radio Science, 18, 477-492, 1983. Fox, M W., and C. Blundell, "Automatic sealing of digital ionograms", Radio Science, 24, 747-761, 1989. Tripnthi ,Y., "Autoseale software eomputerized processing fi'om years of hourly data comparison", Proceedings of Session G5 at the XXVth Cnmeral Assembly of the International Union of Radio Science (URSI), Lille, France, August 28 - September 5, 22-29, 1996. Tsai, L. C., F. T B~key,. and J. Y. Liu "Automatic ionogram trace identification using fuzzy classification toahniques", Proeo~iing~ of Session G5 at the XXVth General Assembly of the International Union of Radio Science (URSI), Lille, France, August 28 - September 5, 4550,1996.
C. Scotto: A Method for Processing lonograms
rI
,,,
•
Fig. 1 The ionogram used for the automatic scaling. This ionogram has been acquired by a DPS 42. The quality of the image has been artificially decreased by adding random noise. The information about polarization has not been considered.
..i
Fig. 2 The ionogram after the resizing procedure introduced to perform the comparison Coy correlation method) with the typical shapes of F2 traces.
369
370
C. Scotto: A Method for Processing lonograms
Fig. 3 The matrices of correlation found for each of the standard traces considerecL For each case the position of the trace has been assumed where the correlation is maximum (a,b,c,d). At the end the absolute maximum has been considered (e). For the first time this procedure has been applied for the detection of the most evident trace.
Fig. 4 The same as figure 3, with reference to the detection of the less evident trace
i.Ikgl
.f
C. Scotto:A Methodfor ProcessingIonograms
371
0
Fig. 5 The points used to build up the analytical limctions that approximate the ionogram traces. In red the points for ordinary trace, in blue for extraordinary trace.
° .
. •
i
.... ~id4~ :2~" Fig. 6 The analytical functions found for the F2 traces by minimum square method. Tangent transmission curve is also indicated.
Fig. 7 The matrix of correlation found for the preliminary detection of the ionogram traces and the approximate position found.