This survey was made at 34.5MHz using GEETEE, the low-frequency telescope at Gauribidanur [DU90]. This telescope was used in the transit mode, and by performing one-dimensional syn- thesis along the N-S direction the entire observable sky was mapped in a single day. This survey covers the declination range from−50◦to+70◦ and the complete 24 hours of right ascension. The sensitivity of the survey is 5 Jy/beam.
The worst resolution is 42 arcseconds which is easily sufficient for ARIES simulations. As can be seen in figure 3.13, the survey does not cover the whole sky. For our simulations, these areas have been filled with data from Cane’s sky map. As the missing data is in a lowly structured region of the sky, the fact that the filled-in data has a much coarser resolution does not seriously affect the simulation results.
The actual digital data [DSS95] for this sky map was provided by the NCSA Astronomy Digital Image Library [ADI].
Figure 3.12: Sky temperature in K as mapped by Cane’s sky map
Figure 3.13: Sky temperature in K as mapped by the GEETEE sky map. Extremely bright spots are cropped at 10·104K
CHAPTER 3. RIOMETERS 48
3.7
Summary
This chapter introduced the main types of riometers (Relative Ionospheric Opacity Meters), sen- sitive radio receivers connected to antenna systems of varying complexity. Riometers measure absorption, i.e. how cosmic radiation is being absorbed by the Earth’s ionosphere. As well as being an interesting topic for study by themselves, these long-term continuous coverage datasets provide important background information for a wide range of scientific applications.
Sky maps and radio stars help to understand, simulate and verify the signals received by riometers. The sky maps and radio stars introduced in this chapter will be used for these purposes in later chapters.
Functional Simulation of ARIES
In this chapter we introduce a set of programs to simulate the data flow through a Mills Cross type system (see chapter 2, section 2.4) from source to the final beam output. These programs (and the results they produce) help to deepen the understanding of the working principle of a Mills Cross type system such as the one used for ARIES.
The simulations discussed in this chapter will also enable us to examine the signals inside the system at various stages, providing test data even before any hardware has been built. This will help to verify that the Mills Cross approach will indeed work as expected and that the suggested approach is capable of delivering results as expected.
The fact that this simulation is done at signal level implies that it is not possible to simulate long periods of time due to the amount of processing power and storage space required. For the same reasons, the simulation cannot be carried out in real-time, and there is a practical limit to the number of sources that can be simulated. Chapter 5 will introduce a different simulation that is geared towards determining estimates for the required integration time in a realistic situation, but the simulations in chapter 5 will not simulate the whole reception process but only the final cross-correlation stage. In particular, the simulations presented here include knowledge about the direction of incoming signals and about beamforming, all of which are details that are beyond the scope of the simulations in chapter 5.
4.1
Data Flow
See figure 4.1 for a general description of the data flow through the simulation. The ‘magnetic disk’ symbols represent data that is immediately accessible as files on the hard drive whereas
CHAPTER 4. FUNCTIONAL SIMULATION OF ARIES 50
the rectangular boxes describe a data source or data processing step.
The whole simulation assumes a fixed operating frequency (38.2MHz by default, though this can be changed easily, see section 4.2). All signals are oversampled 32 times (again, this can be changed by modifying the program source code). Where necessary, linear interpolation is performed, see the description in section 4.2. The following sections describe each stage of the simulation in more detail. They relate directly to the description of the beamforming process for a Mills Cross in chapter 2, section 2.4.
4.1.1 Reception
This stage simulates the signal path from far away signal sources (representing incoming cos- mic radiation from the galaxy as well as the cosmic radiation background) down to reception through an arbitrary number of aerials on the ground, see figure 4.2. The signal sources can be random noise sources of different bandwidths as well as simple sinusoidal or step sources (the latter being mainly useful for program testing purposes). All noise sources are located on a (hemi-)sphere centred on the centre of the antenna system (see section 4.1.2), which forms the origin of the model’s Cartesian coordinate system. The ionosphere is indirectly taken care of by adjusting the signal intensity from each noise source as required. Other ionospheric effects apart from signal attenuation (e.g. scintillation, variable delays) are not taken into account for this model, since simulating ionospheric propagation is not the goal of this simulation, but rather the understanding of the beamforming process for a Mills Cross type antenna system.
The signals from these sources are then received by aerials on the ground. These aerials can be simulated at arbitrary locations (see section 4.2 for details). For the discussions presented in the sections to follow, we use the layout of a 32+32 element Mills Cross antenna just like the real ARIES antenna layout. We use aerials with isotropic radiation patterns, since the beams are mainly influenced by the array factors, not by individual element radiation patterns (see chapter 2). Each aerial receives the sum of all the signals coming from all different sources, each one delayed appropriately depending on the relative position of aerial and signal source, as described in section 2.3.2 in chapter 2 (see especially figure 2.1).
The composite signal from all the sources looks different to each aerial due to the fact that each aerial is located at a different location. The digital representation of this signal is stored in a separate file for each aerial. This will result inn files for nsimulated aerials (n=64 in
simulation is usually run for a given number of sampless, resulting innoutput files withslines each.
These files are by default calledaerial<n>, n being the aerial number. These files represent the output of stage 1 (the reception stage) of the simulation and can either be examined manually or fed into stage 2 (the beamforming stage), see below.