6/16/2010 – TRACKING

I’m completely amazed at how well the transmitter/receiver worked! For only a few milliwatts, I was able to track that thing all the way from takeoff to landing in Gainesville, FL a few hundred miles away. Here is the data assembled in a special, annotated way!

CLICK HERE to view the signal tracked from Gainesville, FL

ANALYSIS: the text on the image describes most if it, but one of the most interesting features is the “multipathing” during the final moments of the descent, where the single carrier signal splits into two. I believe this is due to two Doppler shifts: (1) as the distance between the falling transmitter and the receiver is decreasing, producing a slight in increase in frequency, and (2) a signal reflected off of a layer of the atmosphere above the craft (the ionosphere?) before it gets to the receiver, the distance of which is increasing as the craft falls, producing a decrease in frequency. I’ll bet I can mathematically work backwards and determine how high the craft was, how fast it was falling, and/or how high the layer of the reflecting material is – but that’s more work than this dental student is prepared to do before his morning coffee!

HERE IS SOME AUDIO of some of the strongest signals I received. Pretty good for a few milliwatts a hundred miles away! [beeps.ogg]

6/16/2010 – THE FLIGHT

The launch:

This is the design team:

Walking the balloon to its launch destination at NASA with an awesome rocket (Saturn 1B – identified by Lee, KU4OS) in the background.

The team again, getting ready for launch. I’ve been informed that the reason their hands are up is to prevent the balloon from tilting over too much. I’d imagine that a brush with a grass blade could be bad news for the project!

Last minute checks – you can see the transmitter and battery holders for it taped to the Styrofoam.

The transmitter in its final position. Note the coil of yellow wire. That serves as a rudimentary “ground” for the antenna’s signal to push off of. I wasn’t very clear on my instructions on how to make it. I meant that it should be a huge coil wrapped around the entire payload (as large as it can be), which would have probably produced a better signal, but since I was able to capture the signal during the whole flight it turned out to be a non-issue.

The antenna can be seen dropping down as a yellow wire beneath the payload. (arrow)

Awesome photo.

Launch! Look how fast that balloon is rising!

It’s out of our hands now. When I got the text message that it launched, I held my breath. I was skeptical that the transmitter would even work!

One of the students listening to my transmitter with QRSS VD software (score!)

Video capture from an on-board camera was also attempted (900MHz), but from what I hear it didn’t function well for very long.

6/15/2010 – IMPROVED BUILD

Here you can see me (center arrow) showing the students how to receive the Morse code signal sent from the small transmitter (left arrow) using a laptop running QRSS VD (my software) analyzing audio from and an Icom706 mkII radio receiver attached to a dipole (right arrow).

I amped-up the output of the oscillator using an octal buffer chip (74HC240) with some decent results. I’m pleased! It’s not perfect (it’s noisy as heck) but it should be functional for a 2 hour flight.

Closeup of the transmitter showing the oscillator at 29.4912 MHz, the Atmel ATTiny44a AVR microcontroller (left chip), octal buffer 74HC240 (right chip), and some status lights which blink as the code is executed.

This is my desk where I work from home. Note the styrofoam box in the background – that’s where my low-power transmitter lives (the one that’s spotted around the world). All I needed to build this device was a soldering iron.

Although I had a radio, it is not capable of receiving 29MHz so I was unable to test the transmitter from home. I had to take it to the university to assess its transmitting capabilities.

At UF I used an oscilloscope to measure the waveform of the transmitter.

I connected the leads to the output of the transmitter, shorted by a 39ohm resistor. By measuring the peak-to-peak voltage of the signal going into a resistor, we can measure its power.

Here’s the test setup. The transmitter is on the blue pad on the right, and the waveform can be seen on the oscilloscope on the upper left.

Here’s a closer view.

With the amplifier off, the output power is just that of the oscillator. Although the wave should look like a sine wave, it’s noisy, and simply does not. While this is unacceptable if our goal is a clean radio signal with maximum efficiency, this is good enough to be heard at our target frequency. The PPV (peak-to-peak voltage) as seen on the screen is about 100mV. Since I’m using a x10 probe, this value should be multiplied by 10 = 1V. 1V PPV into 39 ohms is about 3 milliwatts! ((1/(2*2^.5))^2/39*1000=3.2). For the math, see this post

With the amplifier, the output is much more powerful. At 600mV peak-to-peak with a 10x probe (actually 6V peak-to-peak, expected because that’s the voltage of the 4xAAA battery supply we’re using) into 39 ohms we get 115 millivolts! (6/(2*2^.5))^2/39*1000=115.38.

Notes about power: First of all, the actual power output isn’t 115mW. The reason is that the math equations I used work only for pure sine waves. Since our transmitter has multiple waves in it, less than that power is going to produce our primary signal. It’s possible that only 50mW are going to our 29MHz signal, so the power output assessment is somewhat qualitative. Something significant however is the difference between the measured power with and without the amplifier. The 6x increase in peak-to-peak voltage results in a 36x (6^2) increase in power, which is very beneficial. I’m glad I added this amplifier! A 36 times increase in power will certainly help.

The final schematic is here:

6/14/2010 – THE BUILD

Last week I spoke with a student in the UF aerospace engineering department who told me he was working with a group of high school students to add a payload to a high-altitude balloon being launched at (and tracked by) NASA. We tossed around a few ideas about what to put on it, and we decided it was worth a try to add a transmitter. I’ll slowly add to this post as the project unfolds, but with only 2 days to prepare (wow!) I picked a simplistic design which should be extremely easy to understand by everyone. Here’s the schematic:

The code is as simple as it gets. It sends some Morse code (”go gators”), then a long tone (about 15 seconds) which I hope can be measured QRSS style. I commented virtually every line so it should be easy to understand how the program works.

#include <avr /io.h>
#include <util /delay.h>

char call[]={2,2,1,0,2,2,2,0,0,2,2,1,0,1,2,0,2,0,2,2,2,0,1,2,1,0,1,1,1,0,0};
// 0 for space, 1 for dit, 2 for dah

void sleep(){
  _delay_ms(100); // sleep for a while
  PORTA^=(1<<PA1); // "flip" the state of the TICK light
}

void ON(){
 PORTB=255; // turn on transmitter
 PORTA|=(1<<PA3); // turn on the ON light
 PORTA&=~(1<<PA2); // turn off the ON light
}

void OFF(){
 PORTB=0; // turn off transmitter
 PORTA|=(1<<PA2); // turn on the OFF light
 PORTA&=~(1<<PA3); // turn off the OFF light
}

void ID(){
        for (char i=0;i<sizeof(call);i++){
                if (call[i]==0){OFF();} // space
                if (call[i]==1){ON();} // dot
                if (call[i]==2){ON();sleep();sleep();} // dash
    sleep();OFF();sleep();sleep(); // between letters
        }
}

void tone(){
 ON(); // turn on the transmitter
 for (char i=0;i<200;i++){ // do this a lot of times
  sleep();
 }
 OFF();sleep();sleep();sleep(); // a little pause
}

int main(void) // PROGRAM STARTS HERE
{
    DDRB = 255; // set all of port B to output
 DDRA = 255; // set all of port A to output
 PORTA = 1; // turn on POWER light

 while (1){ // loop forever
  ID(); // send morse code ID
  tone(); // send a long beep
 }
}

I’m now wondering if I should further amplify this signal’s output power. Perhaps a 74HC240 can handle 9V? … or maybe it would be better to use 4 AAA batteries in series to give me about 6V. [ponders] this is the schematic I’m thinking of building.

UPDATE

This story was featured on Hack-A-Day! Way to go everyone!

The photo above is the signal of my (AJ4VD) little homemade transmitter in Gainesville, Florida, USA (using a 20-ft piece of wire inside my apartment as an antenna) detected by ON5EX in Belgium. It makes me happy. It reminds me that some of the projects I work on succeed, which gives me motivation to continue pursuing the ones which currently challenge me.

def detrend(data,degree=10):
	detrended=[None]*degree
	for i in range(degree,len(data)-degree):
		chunk=data[i-degree:i+degree]
		chunk=sum(chunk)/len(chunk)
		detrended.append(data[i]-chunk)
	return detrended+[None]*degree

However, this method is extremely slow. I need to think of a way to accomplish this same thing much faster. [ponders]

UPDATE: It looks like I’ve once again re-invented the wheel. All of this has been done already, and FAR more efficiently I might add. Simply:

import scipy.signal
ffty=scipy.signal.detrend(ffty)

Now I’m looking into scipy.signal.triang()

These concepts are simple to visualize when graphed. Here I’ve written a short Python script to listen to the microphone (which is being fed a 2kHz sine wave), perform the FFT, and graph the real FFT component, imaginary FFT component, and their sum. The output is:

Of particular interest to me is the beautiful complementarity of the two curves. It makes me wonder what types of data can be extracted by the individual curves (or perhaps their difference?) down the road. I wonder if phase measurements would be useful in extracting weak carries from beneath the noise floor?

Here’s the code I used to generate the image above. Note that my microphone device was set to listen to my stereo output, and I generated a 2kHz sine wave using the command speaker-test -t sine -f 2000 on a PC running Linux. I hope you find it useful!

import numpy
import pyaudio
import pylab
import numpy

### RECORD AUDIO FROM MICROPHONE ###
rate=44100
soundcard=1 #CUSTOMIZE THIS!!!
p=pyaudio.PyAudio()
strm=p.open(format=pyaudio.paInt16,channels=1,rate=rate,\
			input_device_index=soundcard,input=True)
strm.read(1024) #prime the sound card this way
pcm=numpy.fromstring(strm.read(1024), dtype=numpy.int16)

### DO THE FFT ANALYSIS ###
fft=numpy.fft.fft(pcm)
fftr=10*numpy.log10(abs(fft.real))[:len(pcm)/2]
ffti=10*numpy.log10(abs(fft.imag))[:len(pcm)/2]
fftb=10*numpy.log10(numpy.sqrt(fft.imag**2+fft.real**2))[:len(pcm)/2]
freq=numpy.fft.fftfreq(numpy.arange(len(pcm)).shape[-1])[:len(pcm)/2]
freq=freq*rate/1000 #make the frequency scale

### GRAPH THIS STUFF ###
pylab.subplot(411)
pylab.title("Original Data")
pylab.grid()
pylab.plot(numpy.arange(len(pcm))/float(rate)*1000,pcm,'r-',alpha=1)
pylab.xlabel("Time (milliseconds)")
pylab.ylabel("Amplitude")
pylab.subplot(412)
pylab.title("Real FFT")
pylab.xlabel("Frequency (kHz)")
pylab.ylabel("Power")
pylab.grid()
pylab.plot(freq,fftr,'b-',alpha=1)
pylab.subplot(413)
pylab.title("Imaginary FFT")
pylab.xlabel("Frequency (kHz)")
pylab.ylabel("Power")
pylab.grid()
pylab.plot(freq,ffti,'g-',alpha=1)
pylab.subplot(414)
pylab.title("Real+Imaginary FFT")
pylab.xlabel("Frequency (kHz)")
pylab.ylabel("Power")
pylab.grid()
pylab.plot(freq,fftb,'k-',alpha=1)
pylab.show()

After fighting for a while long with a “shifty baseline” of the FFT, I came to another understanding. Let me first address the problem. Taking the FFT of different regions of the 2kHz wave I got traces with the peak in the identical location, but the “baselines” completely different.

Like many things, I re-invented the wheel. Since I knew the PCM values weren’t changing, the only variable was the starting/stopping point of the linear sample. “Hard edges”, I imagined, must be the problem. I then wrote the following function to shape the PCM audio like a triangle, silencing the edges and sweeping the volume up toward the middle of the sample:

def shapeTriangle(data):
	triangle=numpy.array(range(len(data)/2)+range(len(data)/2)[::-1])+1
	return data*triangle

After shaping the data BEFORE I applied the FFT, I made the subsequent traces MUCH more acceptable. Observe:

Now that I’ve done all this experimentation/thinking, I remembered that this is nothing new! Everyone talks about shaping the wave to minimize hard edges before taking the FFT. BAH! Another case of me re-inventing the wheel because I’m too lazy to read others’ work. However, in my defense, I learned a lot by trying all this stuff — far more than I would have learned simply by copying someone else’s code into my script. Experimentation is the key to discovery!