Polyphemus

Just a quick update.

New Python code to display spectrum also with a heat-map.

from rtlsdr import RtlSdr
from matplotlib import mlab as mlab
import matplotlib.pyplot as plt
import os
from tkinter import *


# SETTINGS
GAIN = 4
SAMPLE_RATE = 2.4e6
F_CORRECTION = 60
DATA_RES = 128
try:
    sdr = RtlSdr()
except:
    print("Error: cannot initialize the SDR device")
    exit(0)

#ASK FOR FREQUENCIES
os.system("clear")
print("Insert initial frequency [MHz]: ", end="")
CENTER_FREQ = int(input())*1e6
print("Insert final frequency [MHz]: ", end="")
END_FREQ = int(input())*1e6

#CONFIGURATION
sdr.sample_rate = SAMPLE_RATE
sdr.center_freq = CENTER_FREQ
sdr.freq_correction = F_CORRECTION
sdr.gain = GAIN
garbage = sdr.read_samples(DATA_RES * 1024)
step = 2.5e5
half_step = step/2
center_f_arr = []
n = int((END_FREQ - CENTER_FREQ)/step)


def getdata():
    pow_arr = []
    freq_arr = []
    for k in range(0,n):
        sdr.center_freq = CENTER_FREQ + (step*k)
        center_f_arr.append((CENTER_FREQ + (step*k))/1e6) #save the central frequency for later
        samples = sdr.read_samples(DATA_RES * 1024)

        power, psd_freq = mlab.psd(samples, NFFT=1024, Fs=sdr.sample_rate/1e6)
        psd_freq = psd_freq + sdr.center_freq/1e6

        for i in range(0, len(psd_freq)):
            if psd_freq[i] < (sdr.center_freq+half_step)/1e6 and psd_freq[i] > (sdr.center_freq-half_step)/1e6:
                freq_arr.append(psd_freq[i])
                pow_arr.append(power[i])

        if(len(freq_arr) > 536870000):
            print("Fatal error: trying to store too much data")
            exit(0)


    i = 0
    for e in freq_arr:
        if e in center_f_arr:
            pow_arr[i] = pow_arr[i-1]
            pow_arr[i+1] = pow_arr[i+2]
            pow_arr[i-1] = pow_arr[i-2]
        i=i+1
    return freq_arr,pow_arr
 

#ask for data
freq_arr,pow_arr = getdata()

#create 2d map
mappa = [[0 for x in range(len(pow_arr))] for y in range(len(pow_arr))] 
for i in range(0, len(pow_arr)):
    for j in range(0, len(pow_arr)):
        mappa[i][j] = pow_arr[j]


f, axarr = plt.subplots(2)
axarr[0].plot(freq_arr, pow_arr, color="green")
c = axarr[1].imshow(mappa, cmap='hot', interpolation='nearest',origin ='lower', aspect='auto')
axarr[1].axis("off")
f.colorbar(c)
plt.show()

Output plot:

Just a quick update here.

I've been messing around with the RTL-SDR Python Library to get some readings from the SDR dongle.

In the end, I managed to make the first version of code that takes two frequencies as inputs, and after some time shows me the spectrum results gathered between those two frequencies.

The code has been developed to remove the typical "central frequency spike" caused by the 0MHz reading and to be as flat as possible between multiple readings, which is necessary because one reading only has 1MHz of bandwidth.

from rtlsdr import RtlSdr
from matplotlib import mlab as mlab
import matplotlib.pyplot as plt
import os

try:
	sdr = RtlSdr()
except:
	print("Error: cannot initialize the SDR device")
	exit(0)

os.system("clear")
print("Insert initial frequency [MHz]: ", end="")
CENTER_FREQ = int(input())*1e6

print("Insert final frequency [MHz]: ", end="")
END_FREQ = int(input())*1e6

GAIN = 4
SAMPLE_RATE = 2.4e6
F_CORRECTION = 60
DATA_RES = 128

pow_arr = []
freq_arr = []

# configure device
sdr.sample_rate = SAMPLE_RATE
sdr.center_freq = CENTER_FREQ
sdr.freq_correction = F_CORRECTION
sdr.gain = GAIN
garbage = sdr.read_samples(DATA_RES * 1024)

step = 2.5e5
half_step = step/2
center_f_arr = []
n = int((END_FREQ - CENTER_FREQ)/step)

#init loading bar
bar = "["
for i in range(1,n+1):
	bar = bar + " "
bar = bar + "]"

#main loop
for k in range(0,n):
	sdr.center_freq = CENTER_FREQ + (step*k)
	center_f_arr.append((CENTER_FREQ + (step*k))/1e6) #save the central frequency for later
	samples = sdr.read_samples(DATA_RES * 1024)

	power, psd_freq = mlab.psd(samples, NFFT=1024, Fs=sdr.sample_rate/1e6)
	psd_freq = psd_freq + sdr.center_freq/1e6

	for i in range(0, len(psd_freq)):
		if psd_freq[i] < (sdr.center_freq+half_step)/1e6 and psd_freq[i] > (sdr.center_freq-half_step)/1e6:
			freq_arr.append(psd_freq[i])
			pow_arr.append(power[i])
	
	os.system("clear")
	string_list = list(bar)
	string_list[k+1] = "="
	bar = "".join(string_list)
	print(bar)
	print("Frequency: ", end="")
	print(psd_freq[i])

	if(len(freq_arr) > 536870000):
		print("Fatal error: trying to store to much data")
		exit(0)


i = 0
for e in freq_arr:
	if e in center_f_arr:
		pow_arr[i] = pow_arr[i-1]
		pow_arr[i+1] = pow_arr[i+2]
		pow_arr[i-1] = pow_arr[i-2]
	i=i+1

print("\n")
print(len(freq_arr))
print("\n")
plt.plot(freq_arr, pow_arr)
plt.plot(END_FREQ/1e6, 0.005)  #noise visual filter
plt.show()

 It's just a very alpha version of the code and needs a bit more work, but for now and for some early testing, it's enough.

News
I wanted to give you a quick update on the radio telescope development. 

I've just received some new RF components that I'll be installing over the next few days.

These comprehend:

• Various SMA cables and connectors
• Noolec SawBird+ H1 LNA
• RTL-SDR Blog V3 (should be here tomorrow)

Also, I started designing the Feed Antenna of the dish. Basically, a can-antenna
designed to have a lower cut-off frequency of 1212MHz and an upper cut-off
frequency of 1582MHz.
[link to the design tool]

Noolec SawBird+ H1 LNA
Nooelec SAWbird+ H1 is a SAW Filter & Ultra-Low Noise Amplifier (LNA) Module for
Hydrogen Line (21cm) applications with a center frequency of 1420MHz.
Some key features of this LNA are:
• +40dB of RF gain at 1420MHz
• 0.8dB noise figure at 1420MHz
• +3.3V-5V single supply

If you don’t know what an LNA is you should check out this link. I will upload a more detailed document in the “Insights” section of the repository on GitHub where I’ll talk about LNAs.
[link to this LNA datasheet]

RTL-SDR Blog V3 

The RTL-SDR Blog V3 is a key component in our project setup. It's essentially a software-defined radio  (SDR) dongle built around the Realtek RTL2832U chipset. 

Widely adopted by hobbyists and professionals, it serves a range of purposes, from radio monitoring to spectrum analysis and amateur radio activities. 

Its affordability and compatibility with open-source software make it an ideal choice for my project's needs. I will post more insights on this device as the project evolves. 

My idea is to write Python code to read data from this dongle to enable more interesting data processing.

News
In the past few days, I've had the opportunity to order online and then assemble
the parabolic antenna for the radio telescope. It has a diameter of 1.2m, a
depth of about 20cm, and therefore, a focal point height of approximately 45cm.
The antenna was sold with a simple aluminium stand on which to mount the dish and
which allows for adjusting the antenna's pointing angle.
The only thing is that it's not sold together with its metal LNB Holder ring. No
big deal though, because it's a piece I would have built anyway in order to
accommodate my custom receiver (Feed Antenna) which will then receive the
amplified radiation from the dish.

Why a parabolic antenna?
Unlike other types of directional antennas, such as Yagi antennas, these allow for the amplification of a much wider signal band.
This will enable the radio telescope to study other astronomical frequencies in the future, as well as the Hydrogen Line. Moreover, this type of antenna guarantees a high amplification factor while still maintaining relatively small dimensions.
This one, in particular, is a primefocus parabolic antenna, meaning that the focal point of the antenna (where the receiver will be positioned) is at the central position.
More commonly seen are offset parabolic antennas, where the focal point and LNB are at the bottom of the antenna. However, these are more difficult to point towards a particular target.

This first report aims to introduce the design and building phase of the entire
project.

What is a radio telescope?
A radio telescope is a specialized antenna and radio receiver used to detect
radio waves from astronomical radio sources in the sky.
Radio telescopes are the main observing instrument used in radio astronomy,
which studies the radio frequency portion of the electromagnetic spectrum
emitted by astronomical objects, just as optical telescopes are the main
observing instruments used in traditional optical astronomy which studies the
lightwave portion of the spectrum coming from astronomical objects.

Which astronomical object are you aiming to study?
Initially, I aim to study the Hydrogen Line (also known as the 21-centimeter
line) emitted by the Milky Way.
This spectral line provides crucial insights into the distribution and movement
of hydrogen gas within our galaxy.
Additionally, the radio telescope will be designed for versatility, allowing for
easy adaptation to explore other frequencies and analyze various celestial
objects.

How will the radio telescope be constructed?
The construction phase of the radio telescope will be divided into two parts. In
the first part, it will be built using technologies already available on the
market and accessible to the public. This is to assess both the feasibility of
subsequent steps and to become familiar with the world of radio astronomy
through devices that have already been tested. In the second phase, I will
replace some of these technologies with devices designed and built by myself.
This way, I should be able to also verify the difference in quality of the radio
signals I receive with my devices compared to those already available on the
market.

What is the key objective you aim to achieve?
The objective of this project is to create a relatively cost-effective radio
telescope capable of yielding scientifically valid and interesting results.
Additionally, as the project originated from reading "Basics of Radio Astronomy
for the Goldstone-Apple Valley Radio Telescope," a document from NASA dated
April 1998, some of the goals will involve applying the physics and engineering
principles learned from that document.