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MODELING THE F REGION IONOSPHERIC PEAK HEIGHT VARIATIONS OVER
MALAYSIA BY ANTENNA PATTERN SYNTHESIS TECHNIQUE
ZETI AKMA BINTI RHAZALI
Thesis submitted in fulfilment of the requirements
for the award of the degree of
Doctor of Philosophy in Electrical Engineering
Faculty of Electrical and Electronic Engineering
UNIVERSITI MALAYSIA PAHANG
SEPTEMBER 2014
vi
ABSTRACT
The ionospheric F region over Malaysia is still an issue to many radio communication
enthusiasts. The actual height of this layer is not well defined. Models available are
mostly reliable for temperate zones. This thesis describes the determination of the actual
F layer height and proposed a unique model to represent the height variations. The
ionospheric F region is observed via ionograms, produced by the ionosonde operated at
Parit Raja (2oN, 103oW, dip 14.3o), Batu Pahat, Malaysia. The ionogram gives the
virtual height representation of the ionosphere. POLAN ionogram inversion program is
used to determine the real height of the ionospheric layer. The observations are held
during period of moderate to low solar activity of solar cycle 23 (2005 to 2010).
However, in this work, only hourly data of March, June, September, and December,
2006 and 2007, are examined. The data are statistically analysed to summarize their
main characteristics. The actual height of the F layer is determined from the median
values and the coefficient of variability quantifies the height deviations. To derive the
mathematical representation of the variations, the least-squares regression technique is
used to fit functions to the median data. The best fit function is the descriptive model
that describes the variations. A new model of ionospheric height variations is also
proposed on the same basis. The ionospheric height time variation which is a cyclic
event is re-represented in polar coordinate form. The cyclic representation which
approximates an antenna radiation pattern allows the development of antenna equivalent
model of peak height variations. The association of ionospheric height variations to the
radiation pattern of antenna array is the novelty idea of this study. The observation
results indicate that the median height of peak electron density, hmax, varies from 420
km in June to 550 km in other months during noon time. The night-time average heights
rest around 300 km for all months. The daytime peak is found highest in December
solstice season and lowest in June season while post sunset peaks are not seen during
this period. The descriptive mathematical model of diurnal variations shows that the
variations fit well into a four-term Fourier series model. The two-element arrays with
array spacing in the x-direction of /8, and phase of /3, and with element spacing in
the y-direction of /4, and phase of zero, is the optimal array configuration which
signifies the variations. The results show that an array of two-element arrays antenna is
suitable to represent the ionosphere peak height variations over Malaysia during
moderate to low solar activity period.
vii
ABSTRAK
Rantau F ionosfera merentasi Malaysia masih menjadi isu kepada kebanyakan
pengguna komunikasi radio. Ketinggian sebenar lapisan ini belum dapat dipastikan.
Model-model yang ada pula cenderung untuk kegunaan di zon bersuhu. Tesis in
menjelaskan penentuan ketinggian sebenar lapisan F dan mensyorkan sebuah model
unik sebagai paparan kepelbagaian ketinggian. Rantau F ionosfera diperhatikan melalui
ionogram, hasil cerapan yang diperolehi daripada ‘ionosonde’ yang beroperasi di Parit
Raja (2oN, 103oW, dip 14.3o), Batu Pahat, Malaysia. Ionogram mempaparkan
ketinggian maya lapisan ionosfera. Perisian POLAN digunakan untuk menukar kepada
ketinggian sebenar lapisan ini. Pencerapan telah dilakukan dalam tempoh aktiviti solar
sederhana hingga rendah, pada kitaran solar 23 (2005-2010). Bagaimanapun, untuk
kajian ini, hanya ionogram dalam sela masa jam bagi bulan Mac, Jun, September, dan
Disember, 2006 dan 2007, diteliti. Analisa statistik digunakan untuk menentukan ciri
penting data tersebut. Ketinggian lapisan ionosfera diperolehi daripada nilai median
manakala pekali variasi menentukan corak kepelbagaian. Pembangunan model
matematik menggunakan teknik ‘least-squares regression’. Sesuatu fungsi matematik
akan disesuaikan kepada nilai median tersebut. Model matematik diperolehi apabila
fungsi matematik tersebut memberikan penghampiran terbaik. Atas dasar yang sama,
pembangunan model bagi menggambarkan kepelbagaian ketinggian ionosfera juga
dilaksanakan. Kepelbagaian ketinggian lapisan ionosfera terhadap masa adalah suatu
keadaan yang silih berulang. Ia boleh dipaparkan dalam koordinat polar. Paparan
sebegini menghampiri paparan corak radiasi antenna tatasusun justeru pembangunan
model kepelbagaian ketinggian lapisan ionosfera adalah perlu. Kesinambungan di antara
kepelbagaian ketinggian lapisan ionosfera dan corak radiasi antena tatasusun merupakan
idea terbaru yang terhasil dari kajian ini. Keputusan pemerhatian menunjukkan
ketinggian ionosfera, hmax berubah dari 420 km pada bulan Jun kepada 550 km pada
bulan-bulan yang lain semasa waktu tengahari. Purata ketinggian pada waktu malam
pula berada pada paras 300 km. Puncak tertinggi dicapai pada bulan Disember dan
terendah dalam bulan Jun. Model matematik untuk kepelbagaian harian menunjukkan
bahawa model jujukan Fourier 4-terma sangat bersesuaian dengan kepelbagaian ini.
Antena tatasusun dua-elemen dengan jarak susunan /8 dalam arah-x dan fasa /3, dan
jarak elemen /4 dalam arah-y dengan fasa sifar, adalah konfigurasi tatasusun yang
paling optimum untuk menggambarkan kepelbagaian ketinggian ionosfera. Keputusan
kajian menyatakan tatasusun dua-elemen tatasusun adalah paparan yang paling sesuai
untuk kepelbagaian ketinggian ionosfera untuk tempoh aktiviti solar sederhana hingga
rendah.
viii
TABLE OF CONTENTS
Page
SUPERVISOR’S DECLARATION ii
STUDENT’S DECLARATION iii
DEDICATION iv
ACKNOWLEDGEMENTS v
ABSTRACT vi
ABSTRAK vii
TABLE OF CONTENTS viii
LIST OF TABLES xii
LIST OF FIGURES xiii
LIST OF SYMBOLS xvii
LIST OF ABBREVIATIONS xix
CHAPTER 1 INTRODUCTION
1.1 Background 1
1.2 Problem Statement 3
1.3 Objectives 5
1.4 Scope of Work 7
1.4.1 Ionospheric Observation
1.4.2 Data Analysis and Trending
1.4.3 Modeling
7
8
8
1.5 Thesis Outline 8
1.6 Summary 10
CHAPTER 2 LITERATURE REVIEW
2.1 Early Discovery 11
2.2 Ionospheric Research 12
2.2.1 Research in Equatorial Region
2.2.2 Research in Malaysia
16
21
ix
2.3 Ionospheric Electron-Density Profile 22
2.3.1 Peak Electron Density, Nmax
2.3.2 Height of Peak Electron Density, hmax
23
28
2.4 Associating Ionospheric Height Variation to Antenna 30
2.4.1 Array Pattern Synthesis Techniques
2.4.2 Parameterising Ionospheric Height Variations by Array
Design Techniques
32
33
2.5 Summary 34
CHAPTER 3 CHARACTERISING THE IONOSPHERIC F REGION
3.1 Introduction 36
3.2 From Observation to Modeling 37
3.3 Data Collection 38
3.3.1 Radio Sounding Technique
3.3.2 Experimental Setup
3.3.3 The Ionogram
38
40
41
3.4 Data Management and Pre-processing 43
3.4.2 Ionogram Inversion using POLAN Program
3.4.2 Technique used to Manage Empty Data Bins
3.4.3 Data Assimilation
3.4.4 Data Mining
43
49
52
55
3.5 Exploratory Analysis of Data 57
3.6 Modeling the Ionospheric Peak Height Variations 59
3.6.1 The Descriptive Model
3.6.2 Ionospheric Peak Height Variations Model
59
60
3.7 Summary 61
CHAPTER 4 OBSERVATIONAL RESULTS OF THE IONOSPHERE
OVER MALAYSIA
4.1 Introduction 64
4.2 Ionospheric Electron Density Studies 64
4.2.1 Electron-Density Profile
4.2.2 Peak Electron Density, Nmax
4.2.3 Height of Peak Electron Density, hmax 4.2.4 Temporal Variations of Nmax
and hmax
64
68
71
76
x
4.3 Ionospheric Features and Characteristics over Parit Raja 78
4.3.1 F3 layer Features of the Noon time Ionosphere
4.3.2 Spread F and Sporadic E Events
78
83
4.4 Influence of Solar Activity 85
4.4.1 Midday vs. Midnight Profiles 86
4.5 Influence of Geomagnetic Activity 88
4.5.1 Geomagnetic Storms Impact on Plasma Distribution 89
4.6 Ionospheric Variability 92
4.7 International Reference Ionosphere (IRI) Model Verification 94
4.8 Summary 97
CHAPTER 5 ANTENNA PATTERN EQUIVALENCE OF PEAK
HEIGHT VARIATIONS
5.1 Introduction 104
5.2 Characterisation of the Height of Peak Electron Density Variations 105
5.2.1 Introduction
5.2.2 Fourier Components as Approximation to Median Height of
Peak Electron Density Variations
5.2.3 Mathematical Representation
5.2.4 Cyclic Diagram
105
105
112
114
5.3 Antenna Pattern Equivalence of Peak Height Variations 115
5.3.1 Development of the Model
5.3.2 Array of an Array
5.3.3 Closeness of Fit
115
126
133
5.4 Summary 139
CHAPTER 6 CONCLUSIONS
6.1 Introduction 143
6.1.1 Ionospheric Height Variations
6.1.2 Cyclic Diagram
6.1.3 Parameterisation of Ionospheric Height Variations
143
144
144
6.2 Summary 145
6.3 Future Work 147
xi
REFERENCES 149
APPENDICES
A Solar Cycle 23/24 158
B Sample Ionograms 159
C Curve Fitting using Fourier Series Approximation 164
D Catalogue of Array Patterns 188
E List of Publications 193
xii
LIST OF TABLES
Table No. Title Page
2.1 Ionosonde stations in equatorial region 17
3.1 Standard modes of analysis incorporated in POLAN 45
3.2 Solar activity indicator 53
3.3 Geomagnetic activity condition 55
4.1 The daytime and night-time Nmax and hmax values for five
consecutive days of January 2005
88
4.2 Optimal value of median Nmax, and hmax and their corresponding
standard deviations
97
5.1 RMSE values for all representative months 108
5.2 Performance comparison for the four representative months
under different geometrical configuration
125
5.3 Performance comparison for the four representative months
under different geometrical configuration
134
5.4 Standard deviations 135
5.5 Numerical results of the antenna equivalence of hmax variations
(2006) giving the magnitude, G dB, and difference, dB
141
5.6 Numerical results of the antenna equivalence of hmax variations
(2007) giving the magnitude, G dB, and difference, dB
142
5.7 Results showing the coefficients of Fourier series
approximation to March median hmax variations
164
5.8 Results showing the coefficients of Fourier series
approximation to June median hmax variations
170
5.9 Results showing the coefficients of Fourier series
approximation to September median hmax variations
176
5.10 Results showing the coefficients of Fourier series
approximation to December median hmax variations
182
5.11 Array factor of N = 2, 3, and 4 for different element spacing, d 188
5.12 Array factor of N = 2 for different element spacing, d, and
progressive phase shift,
190
xiii
LIST OF FIGURES
Figure No. Title Page
2.1 (a) An illustration of the equatorial plasma fountain effect
(Bilitza, undated) (b) Latitudinal variation of electron density at
fixed height
19
2.2 Equatorial atmosphere ionosphere coupling processes 20
2.3 Sample electron-density profile 23
2.4 (a) The buildup of the ITS-78 model (b) The Bradley and
Dudeney (1973) model
25
2.5 The normalized electron density N(h)/No according to Chapman’s
theory
26
2.6 The buildup of the IRI model 28
3.1 Sequence of procedures to final model development 37
3.2 Radio sounding principle 38
3.3 Experimental setup 40
3.4 Sample (a) daytime and (b) night-time ionograms of Parit Raja
(THO)
42
3.5 POLAN Output 46
3.6 Sample scaled ionogram and real-height profile of Parit Raja
obtained using POLAN with (a) START = -1 (b) START = 0 (c)
START = 3 d) START = 90
48
3.7 Real-height profiles of Parit Raja using different AMODE values 49
3.8 Linear fit overestimates the missing data of Parit Raja 50
3.9 Interpolation shows better approximation in substituting missing
data of Parit Raja
51
3.10 Comparison of pre-processing techniques to data of Parit Raja 52
3.11 Geomagnetic activity conditions 56
3.12 Solar activity conditions 57
3.13 The parameterisation process 61
4.1 Electron density profiles showing progressive development of F
layers
66
xiv
4.2 The peak electron density, Nmax, diurnal variations of (a) March
Equinox (b) June Solstice (c) September Equinox and (d)
December Solstice during moderate solar activity (2006).
Discontinuities in June plots are due to null data resulting from
high irregularities that blankets any ground observation
69
4.3 Seasonal patterns of median Nmax during moderate solar activity 70
4.4 The height of maximum electron density, hmax diurnal variations
of (a) March Equinox (b) June Solstice (c) September Equinox
and (d) December Solstice during moderate solar activity (2006).
Discontinuities in June plots are due to null data resulting from
high irregularities that blankets any ground observation
72
4.5 Seasonal patterns of median hmax during moderate solar activity 73
4.6 Median hmax for four different seasons in (a) 2006 and (b) 2007
during moderate solar activity period
74
4.7 Variability of hmax for four different seasons during low solar
activity period (a) 2006 (b) 2007. The solid line show the median
valued for the year
75
4.8 Temporal variations of Nmax and hmax 77
4.9 The monthly occurrence rate of ionospheric F3 layer over Parit
Raja
79
4.10 The onset and peak occurrences of F3 layer over Parit Raja for
2006-2007
79
4.11 Seasonal variations of ionospheric F3 layer occurrences 80
4.12 Median hmax for four different seasons in (a) 2006 and (b) 2007
during moderate solar activity period
82
4.13 Spread F and sporadic E occurrences 84
4.14 Seasonal patterns of median hmax during moderate solar activity 85
4.15 Sample (a) midday (1200 LT) and (b) midnight (0000 LT)
electron density profiles of five consecutive days of January 2005
87
4.16 Respective maxN and maxh day-to-day variations for December
2006. The dotted lines are the respective monthly medians
90
4.17 Median values of (a) Nmax and (b) hmax under different
ionospheric conditions
91
4.18 Variability of hmax for four different seasons during low solar
activity period (a) 2006 (b) 2007. The solid line show the median
valued for the year
93
xv
4.19 IRI comparison (a) peak electron density (b) height of peak
electron density
95
4.20 Ion composition of the neutral atmosphere 101
4.21 Equatorial Ionosphere Thermosphere System 102
4.22 Sample vertical ion drift pattern for December 2006 103
4.23 Ionograms of 14 January 2005 159
4.24 Ionograms of 15 January 2005 160
4.25 Ionograms of 16 January 2005 161
4.26 Ionograms of 17 January 2005 162
4.27 Ionograms of 18 January 2005 163
5.1 Sample of numerical fit for March 06 106
5.2 Samples showing the confidence bounds for the fitted coefficients 109
5.3 Curve fitting using Fourier Series approximation and the
residuals
111
5.4 hmax variations (a) 2006 (b) 2007 113
5.5 (a) Polar representation of hmax variations (b) Antenna
equivalence hmax variations radiation pattern
114
5.6 Far-field geometry of N-element array of isotropic sources
positioned along the z-axis
116
5.7 Array patterns for array antenna with N = 2, 3, and 4 elements
separated by d = /8, /4, /3, /2, and
122
5.8 Two-element array pattern with element separation, d = /8, /4,
and d = /3 for = 0, /6, /3, and = /2
123
5.9 Array factor of two-element array with d = /8 and = /3
(solid line)
126
5.10 The planar array geometry 128
5.11 Pattern multiplication of two identical arrays (a) linear
configuration (b) multidimensional configuration. Both arrays
have uniform element spacing, d = /8, and progressive phase
shifts, = /3. The total pattern is compared to June 2006
antenna equivalence of peak height variations radiation pattern
130
xvi
5.12 Pattern multiplication of two different arrays (a) linear
configuration (b) multidimensional configuration. Array 1 is a
two-element array with d = /8 and = /3 while Array 2 is
another two-element array with d = /4 and 0 . The total
pattern is compared to June 2006 antenna equivalence of peak
height variations radiation pattern
132
5.13 Antenna equivalence of peak height variations radiation patterns
(solid line). The dotted line shows respective months variations
136
5.14 Difference from the fits for (a) 2006 and (b) 2007 138
5.15 Geometrical configuration of planar array 140
5.16 Samples showing the confidence bounds for the fitted coefficients
(March 2006)
166
5.17 Data fits and residuals (March 2006) 167
5.18 Samples showing the confidence bounds for the fitted coefficients
(March 2007)
168
5.19 Data fits and residuals (March 2007) 169
5.20 Samples showing the confidence bounds for the fitted coefficients
(June 2006)
172
5.21 Data fits and residuals (June 2006) 173
5.22 Samples showing the confidence bounds for the fitted coefficients
(June 2007)
174
5.23 Data fits and residuals (June 2007) 175
5.24 Samples showing the confidence bounds for the fitted coefficients
(September 2006)
178
5.25 Data fits and residuals (September 2006) 179
5.26 Samples showing the confidence bounds for the fitted coefficients
(September 2007)
180
5.27 Data fits and residuals (September 2007) 181
5.28 Samples showing the confidence bounds for the fitted coefficients
(December 2006)
184
5.29 Data fits and residuals (December 2006) 185
5.30 Samples showing the confidence bounds for the fitted coefficients
(December 2007)
186
5.31 Data fits and residuals (December 2007) 187
xvii
LIST OF SYMBOLS
foE Critical frequency of the E layer
foF1 Critical frequency of the F1 layer
foF2 Critical frequency of the F2 layer / Ordinary wave
fxF2 Extraordinary wave
fN Plasma frequency
fc Critical frequency
fo Critical frequency of ordinary wave
fx Critical frequency of extraordinary wave
f Frequency
h Real height
h’ Virtual height
ho Base of the ionosphere
hr Reflection height
maxh Height of peak electron density
hmF2 F2 layer height of peak electron density
H Scale height
N, Ne Number of electron (per meter3)
maxN Peak electron density
NmF2 F2 peak electron density
B0 Thickness of the F2 region
B1 Shape of the F2 region
2)3000( FM Propagation factor
Rz12 12 month running-mean sunspot number
IG12 ionosphere-effective solar index
Ap Daily magnetic index
Kp 3-hour Planetary
c Speed of light
t Time
T Time of flight
Solar zenith angle
xviii
Refractive index
' Group refractive index
a0, an, bn Fourier coefficients
n Number of term (harmonics)
E Electric field
N Number of element
d Element spacing
dx Array spacing
dy Element spacing
Progressive phase shift
Elevation angle
k wave number
r Far field distance
Array phase
Wavelength
O Oxygen
N2 Nitrogen
NO Nitrogen Oxide
xix
LIST OF ABBREVIATIONS
ACE Advanced Composition Explorer
ARTIST Automatic Real Time Ionogram Scaler with True Height
CADI Canadian Advanced Digital Ionosonde
CCIR International Radio Consultative Committee
COSPAR Committee on Space Research
CTIP Coupled Thermosphere-Ionosphere-Plasmasphere
EEJ Equatorial Electrojet
EIA Equatorial Ionization Anomaly
EITS Equatorial Ionosphere-Thermosphere System
ESF Equatorial Spread F
EUV Extreme Ultra-violet
FAIM Fully Analytical Ionospheric Model
GIRO Global Ionospheric Radio Observatory
GPS Global Positioning System
HF High Frequency
HWM Horizontal Wind Model
ICED Ionospheric Conductivity and Electron Density
IONCAP Ionospheric Communication Analysis and Prediction
IRI International Reference Ionosphere
ISR Incoherent Scatter Radars
LT Local Time
MSIS Mass Spectrometer and Incoherent Scatter
MUF Maximum Usable Frequency
NASA National Aeronautics and Space Administration
NHPC N(h) on PC
NOAA National Oceanic and Atmospheric Administration
PARIM Parameterized Regional Ionosphere Model
PIM Parameterized Ionospheric Model
POLAN Polynomial Analysis
RCS Radar Cross Section
xx
RMSE Root Mean Squared Error
SID Sudden Ionospheric Disturbance
SLIM Semi-Empirical Low-Latitude Ionospheric Model
SOHO Solar and Heliospheric Observatory
SPIDR Space Physics Interactive Data Resource
SSE Sum of Squares due to Eerror
SSN Sunspot Number
SUPIM Sheffield University Plasmasphere-Ionosphere Model
TEC Total Electron Concentration
THO Tun Hussein Onn
UHF Ultra High Frequency
URSI International Union of Radio Science
UTC Universal Time
VHF Very High Frequency
VIS Vertical Incidence Sounding
CHAPTER 1
INTRODUCTION
1.1 BACKGROUND
The knowledge on the state of the upper atmosphere, in particular its ionospheric
part, is very important in several applications affected by space weather. The radio
frequency communications and the satellite positioning and navigation systems are the
most affected ones by ionospheric disturbances. In particular, ionospheric disturbances
can cause drastic changes of large-scale to the usable range of high frequency (HF) or
below high frequency bands affecting the standard ground-to-ground and submarine
communication systems. The effects are recognized as loss of communications, change
in area of coverage, low signal power, fading, and error rate change. Fading and error
rate change are also the effect of very high frequency (VHF) or ultra high frequency
(UHF) band, causing disturbances in ground-to-satellite communication systems.
Ionospheric scintillation and dispersion could lead to loss of phase lock and position
errors, which strongly affects the advanced navigation systems. Therefore, to keep
different technical systems functioning in spite of all these effects, specification and
prediction of the state of the upper atmosphere is of significant important and valuable.
The most important property in the ionosphere is the electron density. This
parameter varies considerably with time (sunspot cycle, seasonally, and diurnally),
geographical location (polar cap, auroral zones, equatorial regions), and with certain
solar disturbances (Davies, 1990). Over the last 60 years, continuous and automatic
monitoring of the state of the ionosphere has been carried out extensively with the
worldwide network of ionosonde stations. The ionospheric electron-density profiles are
modeled and their characteristic parameters are presented through global maps. These
2
models are widely used for effective ionospheric study and forecasting. However, in
some regions the discrepancies are highlighted. The models had under or overestimated
densities that may lead to wrong interpretation of the state of the ionosphere. The
accuracy of the data-based model is highly dependent on the availability of reliable data
for the specific region and time (Bilitza et al., 1993). Inadequate comparisons are
obviously seen in particular at low- and equatorial latitudes regions due to scarce
distribution of ionosonde stations. This scenario had raised interest for researchers and
scientists to extend studies over these regions. More ionosonde stations are installed in
equatorial region and their results are valuable inputs to the improvement of these
models. Readers are referred to Chapter 2.2 for further deliberations on this issue.
The ionosphere over this region was described by Rishbeth (2000) as unique as
it exhibits the well-known equatorial ionization anomaly (EIA). This is characterized by
an ionization trough at the magnetic equator and crests on either side at latitudes around
±16o (Appleton, 1946). The cause of the anomaly is by the equatorial plasma fountain
that transfers ionization from around the equator to higher latitudes (Appleton, 1946).
Peculiar features over this region such as the appearance of an additional ionization
layer above the F2 peak, namely the F3 layer during morning-noon period and the post-
sunset peak are results of the above mentioned mechanism (Bailey and Balan, 1996;
Jenkins et al., 1997; Balan et al., 1998). Located in between the geographical equator at
the south and geomagnetic equator in the north, the location of Malaysia is found to be
very strategic to explore such interesting phenomena. The operational of Parit Raja
ionosonde station is a substantial beginning of this exploration. The station was in
operation in December 2004. It is the only ionosonde station in Malaysia that provides
ionosonde data for region close to magnetic equator.
The ionosonde data is a viable resource to describe the vertical profile of the
ionosphere. The data is analysed to determine the actual F layer height and produce
better description of its variations. The height of peak electron density, hmax, is the
height where maximum electron density occurs. Along with the peak electron density,
Nmax, these parameters made up the electron-density profiles. Thus, ionospheric
observation is a vital step in understanding of the ionospheric behavior. This will be
3
further elaborated in the subsequent chapters. A model that characterised the F region
peak density height variations is the outcome of the study.
1.2 PROBLEM STATEMENT
The ionosphere F region, being the most important region of the ionosphere
exist in the upper atmosphere at an altitude range of 200 km to about 1000 km (Davies,
1990). This region is primarily responsible for most skywave propagation of radio
waves, facilitating high frequency, or shortwave radio communications over long
distances as it has the densest electron density and most important exists at all time
(Davies, 1990; Rishbeth and Garriot, 1969). This layer may also cause signal
attenuation to most space related applications, deteriorating the performance of satellite
radio systems. The equatorial F region is also known to be highly variable corresponds
to the processes which control its production, loss, and transport of electrons, especially
at the altitude range above 250 km (Rishbeth and Garriot, 1969; Rishbeth, 2000). The
greatest electron density, Nmax, occurred at higher altitude and the corresponding height
is referred as the height of maximum electron density, hmax (Rishbeth and Garriot,
1969).
Studies on the F layer height of peak electron density, hmax, received less
attention compared to other ionospheric parameters. Unlike critical frequencies, the
actual height determination process is more complex as the electrons are easily drifted.
This thesis reports on three main problems associated with the actual height of
maximum electron density, hmax, which had inspired research on this parameter, as
below:
i) To enhance the actual height analysis studies in Malaysia.
All ionospheric sounding processes provide only virtual height information.
When Zain et al. (2008) observed the appearance of F3 layer over Parit Raja, the
demand for a precise value of actual height of peak electron density becomes
apparent. The F region peak electron density is assumed to occur at 300 km, as
observed in mid-latitude regions, whereas, in equatorial latitude regions, the
4
height of peak electron density has been reported high, between 350 and 500 km
(Bilitza, undated). The assumptions need further justification considering that
Malaysia is located in the vicinity of equatorial ionization anomaly. The actual
height of peak electron density over Malaysia is still unknown. Varying height is
expected in the diurnal pattern of hmax.
The assertion on varying height of the ionosphere over Malaysia requires
research on the height deviation of hmax. The F region hmax variability study is
important to determine the extent of the height deviation from the mean value
under different ionospheric conditions. The dependence of electron density on
solar radiation is known as the main cause of the hmax variability. The effects are
greater under severe solar activities and geomagnetic storms. Any occurrence of
ionospheric disturbances may change the physical properties of the ionosphere.
The F layer may become unstable, fragmented, or even disappear completely.
The electron-density profile is very significant to illustrate the variation of
electron densities with heights. Different shapes of day and night profiles are
observed to gauge better understanding of the physical mechanisms that control
the processes and behavior of the equatorial ionosphere.
Furthermore, the International Reference Ionosphere (IRI) model verification for
Malaysia has not been extensively reported. The IRI model is the most widely
used empirical model for effective ionospheric study and forecasting globally.
The model becomes the first adopted standard specification of ionospheric
parameters by the Committee on Space Research (COSPAR) and the
International Union of Radio Science (URSI) in 1990. The accuracy of IRI
model in presenting equatorial region densities have been reported elsewhere
(Jesus et al., 2011; Yadav et al., 2010; Wichaipanich et al., 2010), however for
Malaysia, there is no activities conducted related to IRI model verification.
5
ii) The classical way of representing hmax temporal variation in the Cartesian
coordinate system is too conventional
In this study, trend analyses are used to illustrate the characteristic variation
patterns. Appropriate mathematical functions are then used to represent the
temporal variations; for a repetitive function, the Fourier series approximation is
suitable to describe the variations. This is a classical way of representing
temporal variations which is usually represented in a rectangular coordinate
system. An alternative representation is introduced where the diurnal height
variation, which is cyclic in nature, can be represented using polar
representation. By using appropriate formulation, the time variation model is
transformed into polar representation.
iii) Lack of a model to signify the ionospheric height variations
A suitable model representing the characteristic parameter is anticipated at the
end of this study. Equivalence antenna pattern model of ionospheric height of
peak density variations based on antenna radiation characteristics is possible
considering the underlying principle of polar representation. This is a novel
approach introduced in this study by parameterization of the ionospheric height
variation using the attributes of array antenna.
In general, further specifications on the actual height of F layer over equatorial
region require thorough studies in this domain. The Parit Raja ionosonde data may
provide good insight into this anonymous scenario. The experimental data sets are
analysed to obtain concrete justifications to the above statements. In addition,
characterisation of this parameter helps to describe the scenario in a more appropriate
manner.
1.3 OBJECTIVES
The quest for actual F region height of peak electron density over Malaysia
instigates studies in this domain. Important attributes of the F region height of peak
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electron density are used to explain the dependency in the actual behavior of this
parameter to the variations in solar activity, and other geographical constraints. The
objectives of this work in addressing the problem statements described in section 1.2
are:
i) To determine the actual ionospheric F region height of peak electron density,
hmax, overhead, describes its variability (diurnal, seasonal, annual) corresponding
to different ionospheric conditions, and investigate the adequacy of IRI model in
explaining the observed densities in equatorial regions.
The actual heights of ionospheric F region during moderate to low solar activity
period are deduced from hourly ionograms of March, June, September, and
December, 2006 and 2007. The representations are based on median data. The
typical behavior of the F region ionosphere is explained and statistical analyses
are used to quantify the expected deviations from that typical behavior. The
variability of ionospheric characteristics with local time, season, and solar
indices, as a result of known changes in ionising sources and atmospheric
composition are clarified. The results of IRI prediction model will be compared
with observational data to establish an empirical correction to the current model,
if exists.
ii) To develop a descriptive model that represents the diurnal characteristics of the
ionospheric F region height of peak electron density over Malaysia and further
enhanced the classical representation.
A simple, numerical model that can be used to calculate approximate profiles
under any required conditions are derived based on experimental evidence using
data sources from the ionosonde. The descriptive model should give fully
smooth and physically realistic variations at all times. The cyclic nature of the
variations would enable new representation in polar form. Enhancement in the
classical way of representing hmax temporal variation is feasible by using
appropriate transformation of the time domain.
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iii) To model an antenna equivalences of peak height variation.
A signature of ionospheric height of peak density variations in this manner may
represent appropriately the ionospheric F region height variations over Malaysia.
The variations can be described by antenna array design parameters such as
number of elements, element separation, and current and phase in each element.
1.4 SCOPE OF WORK
The scope of work is divided into three main categories according to the
research approach. The description for each of the stages is as follows:
1.4.1 Ionospheric Observation
Ionospheric observation is the most fundamental step in preliminary
understanding of the ionosphere. The ionosonde used to probe the ionosphere is located
at Parit Raja (2oN, 103oW, dip 14.3o), Batu Pahat, Malaysia. Radio soundings are
carried out daily at 5 minutes interval to monitor the state of the ionosphere. The
recorded tracings of reflected high frequency radio pulses are observed regularly to
examine the present ionospheric condition. These ionograms, generated by the
ionosonde, shows the virtual height, h’, of the ionospheric layers as a function of plasma
frequency. Proper inversion method is required to obtain the real height, h. Several
programs arise to facilitate this inversion, among which the polynomial analysis
(POLAN) program and NHPC are widely used at present (Liu et al., 1992). Depending
on the instrument type, the POLAN program developed by Titheridge (1985) is used
extensively in this study. The inversion process is manually performed on individual
ionogram. The tediousness of the inversion process is highly vulnerable to error
especially when there are occurrences of ionospheric disturbances (e.g. spread F and
sporadic E). These disturbances may mislead the ionogram interpretation. Knowledge in
physics and chemistry of ionosphere are necessary to facilitate this process. The output
of POLAN is in text file where in this context, it is still considered as raw data.
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1.4.2 Data Analysis and Trending
The peak electron density, Nmax, and height of peak electron density, hmax, are
two important parameters derived from the ionograms using POLAN. Together with the
solar and geomagnetic data, these data are arranged to form a solid database. The data
assimilation process also involves some pre-processing procedures which categorised
the data according to event types and subsequently extract any geomagnetic dependency
data in the final output. The idea is to produce a database which will produce an ideal
approximation of the ionosphere behavior. The ‘processed data’ are also used to draw
the median Nmax and hmax trends. Different conditions could be considered; diurnal
variations (sunrise, noon time, sunset, midnight), seasonal variations (spring, summer,
autumn, winter), and solar activity (high, low) variations. These are various type of
variability that can weigh up any investigation on the ionospheric behavior. This stage
requires high computational skills and MATLAB program is utilized for this purpose.
1.4.3 Modeling
A numerical model of the diurnal trends of median height of peak electron
density variations is needed to calculate approximate variations at all times. In this case,
appropriate mathematical function is used to represent the characteristic variation
patterns. As for a periodic function, Fourier series approximation is the most suitable fit.
The empirical models are then remodeled into suitable representation before a final
model which constitutes to ionosphere height of peak electron density variations can be
established. The configuration of this new model is the novelty of this study.
1.5 THESIS OUTLINE
This thesis is divided into six main chapters. Chapter 1 introduces the main idea
of the research project. The introduction describes the importance of ionospheric studies
in communication aspects which involves either terrestrial or satellite communication
systems. The idea of having comprehensive global ionospheric profiles is also addressed
which then highlights the equatorial ionosphere as one of the challenging region to