Digital Filters

The digital filters are embedded in Spectrum Lab's test circuit. There is one filter for each of the two possible channels, but both channels can be combined into one long processing chain. A filter can be used for many purposes. This chapter describes the basic operation of the filter.
Overview of contents:

• FFT filter (with frequency inverter, -shifter, autonotch, denoiser, various filter types and plugins)
• I/Q processing (for the FFT filter)
• Filter implementation
• Starting and stopping the filter
• Testing a filter
• Interpreter commands for the digital filters

See also: Spectrum Lab's main index ,  circuit window , comb filter .

FFT filter

The FFT-based filters are basically FIR filters, but the filtering is not done in the time domain. The input signal is transformed from the time- into the frequency domain (using the FFT), the spectrum multiplied with the filter's frequency response, and the result is transformed back into the time domain (using the inverse FFT). Though this sounds more complicated than the classic FIR implementation in a DSP, it's actually much faster if the filter has a high order (=a large number of coefficients). And it offers some special options -see the list of operations below- which are otherwise difficult to achieve.

With an FFT-based FIR filter, you can realize increadibly steep transitions, extreme stopband attenuation, and a linear phase - which is almost impossible with a simple FIR- or IIR filter. Since 2006, the filter can additionally move frequencies up or down, and turn USB into LSB (upper / lower sideband). The following list shows the sequence of the operations performed inside the filter:

1. Transform a block of samples from the time- to the frequency-domain (FFT)
2. If loaded and configured as the "first step": Pass the transformed data to the FFT-filter plugin
3. Move frequencies down (option, one of the first steps in the frequency domain when converting "down")
4. frequency-selective limiter (optionally)
5. automatic multi-notch filter (to remove "steady carriers", optionally)
6. denoiser (option.. using spectral subtraction)
7. FILTER (always active, may be bandpass, lowpass, highpass, bandgap, or custom-type).
   In the frequency domain, this is just a multiplication of the samples with the filter's frequency response.
8. Move frequencies up (option, last step in the frequency domain when converting "up")
9. If loaded and configured as the "last step": Pass the transformed data to the FFT-filter plugin
10. Transform back from frequency- to time domain (inverse FFT)

There is an extra tabsheet for the two FFT filters in the filter control window. If you want to use the FFT filter as a simple lowpass, highpass, bandpass or bandgap, select the filter type from the combo box, enter the center- or cutoff frequency and -possibly- the bandwidth in the edit fields (advanced users can also set these parameters through interpreter commands instead of defining them on the panel shown below). One example for controlling the FFT-filter through the interpreter is the "SAQ VLF Receiver" (software defined radio for the VLF band, 3 to 24 kHz).

(screenshot "FFT filter control panel")

Controls for the FFT filter in the filter control window:

• Enabled: If checked, filter block uses the FFT filter (otherwise conventional filter in the time domain)
• Filter type: Select lowpass, highpass, bandpass, band reject or custom here. For the "custom"-type filter, you can draw the frequency response with the mouse in the lower right part of this window (a bit crude still, may be replaced with something better in future).
• FFT size (points): Important for the "resolution" of the filter. For steep edges, very narrow notches, etc use the highest possible value. Downside: The larger the FFT size, the longer the delay introduced by the FFT filter. The FFT size also affects the 'reaction speed' of the autonotch filter. Suggestion: Play around with these parameters to find the best value for your application.. Generally, avoid FFT sizes below 1024.
• Center/Cutoff: For bandpass and band reject filters, enter the center frequency here. For lowpass and highpass, this is the frequency of the -3dB cutoff point.
• Bandwidth: For bandpass and band reject only. Defines the bandwidth (in Hertz) between the -3dB points.
  Note: You can connect the center frequency, the bandwidth control, and the optional shift frequency to SL's frequency markers. This way, you can easily change these values by moving the diamond-shaped frequency markers on the frequency scale. Details in one of the following chapters.
• Slope width: Width of the filter skirts in Hertz. You may find that the steepest possible filter is not always the best - for example, for a morse code filter a smooth filter may "sound" better than a filter with extremely steep edges.
• Frequency shift / direction: Shift frequencies up or down within the FFT filter. More info in these notes about the FFT-based frequency converter. The shift value (offset in Hz) is displayed as a blue vertical line in the graph; the direction as arrows (down=arrow left, up=arrow right). If the frequency shift is enabled, the filter fresponse will be shown in the graph (see below) in black colour at the baseband frequency, and in gray colour at the "high" (converted) frequency. If the direction is "UP", the input signal is filtered first, and frequencies shifted afterwards. If the direction is "DOWN", the frequencies are shifted first, and filtered afterwards. This simplifies the task of switching between transmit and receive, if SL is used as a software-defined radio.
• Frequency inversion range: Mirrors all frequencies (FFT bins) in a certain frequency range. Can be used to convert the upper side band into lower side band and vice versa. Note that due to the sequence of operations inside the FFT-based filter, this happens in the baseband (=low frequency range). The inversion range is displayed as a double-ended green/orange arrow in the graph.

On the "Graph" tab of the FFT-filter control panel, the most important parameters are displayed in graphical form and can be modified with the mouse (by clicking into the graph). Some of the graphic elements can be turned on and off on the "options" tab (next paragraph). Controls on this tabsheet are:

• Selection combo (box in the upper left corner): Select what you want to edit with the mouse (left button) in the graph. You can modify the frequency response, the limiter threshold levels, and some other parameters.
• The button above the graph (labelled "Start Polygon", "First point", "Next point" etc) can be used to toggle between "single point" and "polygon drawing" mode. In Polygon mode, the program calculates a linear interpolatation between two points, which helps to draw a completely new curve, like this:
  - Click on the "Start Polygon" button once, so it shows "First Point..."
  - Do what the button says: Click on the first point of the new curve (usually beginning at the left side of the graph)
  - The button then says "Next point..", and you continue clicking into the diagram to enter the next point.
  The program will automatically calculate everything in between. This works for various graphs in the diagram (custom filter response, threshold levels, etc).
• "Lin" / "Log" : These radio buttons select linear or logarithmic display. Logarithmic is often the better choice due to its large dynamic range. Too low levels can not be seen on a linear scale. The logarithmic scale is in fact "decibel below the clipping point", as in most other parts of Spectrum Lab.
• Other small buttons just left to the graph area can be used to zoom into the graph, and to scroll the displayed frequency range left or right.

The black graph shows the filter response in the baseband, the gray graph is the same but shifted up or down, depending on the frequency-shift settings. Together with the option 'show input spectrum', this feature can be used like the VFO in a software-defined radio.

Less often used controls are on the "options" tab:

• Autonotch: Adds an multi-frequency autonotch to the FFT filter. Function described below.
• Denoiser: A simple denoiser, uses "spectral subtraction" of a constant value from all FFT bins (magnitudes in the frequency domain).
• Frequency-selective limiter : An experimental "signal limiter". All spectrum lines which exceed a certain, individual level (painted as red line into the graph) will be limited to just that level. This may be helpful to reduce man-made interference (strong, steady carriers) in a spectrum where you are interested in the weaker components (like whistlers and other noise-like signals in natural radio recordings). To set the proper threshold levels, turn on the display of the momentary input (green line), and then set the signals in the diagram (using the mouse in "polygon" mode). Everything below the threshold will not be affected (in contrast to the multi-frequency automatic notch, which always rips some of the wanted signals apart). Thanks to Renato Romero for the suggestion ! To listen to the effect of this filter on various kinds of noise, load the configuration file FFT_lim1.usr (it uses the generator as an artificial noise source, turn the generator off to listen to real-world signals).
• Same params for both channels: Only important for stereo mode. If checked, the 2nd channel uses the same filter parameters at the 1st.
• Show input spectrum: If checked, the filter's frequency response is shown in the spectrum graph in the main window (dark green).
• Show output spectrum: If checked, the filter's frequency response is shown in the spectrum graph in the main window (cyan colour).
• I/Q-Input: Inphase and Quadrature input to the filter. Can be used for image-cancelling direct conversion receivers (a bit like "software defined radio") as explained in another chapter. In I/Q-mode, the filter can process negative and positive frequencies, which gives a useable bandwidth of almost 96 kHz for a 96-kHz sampling rate.
• I/Q-Output: Inphase and Quadrature output from the filter. Can be used to drive single-sideband transmitters with little overhead (but beware the caveats resulting from non-perfect soundcard outputs !).  Explained in another chapter.
• Frequency response file: Name of the file in which the frequency response of the "custom"-type filter is saved.
• autonotch speed: A relative measure for the 'speed' of the autonotch filter. A value of 1.0 would mean 'immediate reaction' so the signal will virtually be subtracted from itself. A value of 0.0 means ultimately slow reaction, in fact the notches won't change at all. For listening purposes, 0.02 .. 0.2 are good values, and 0.1 is a good starting point for experimentation.
• denoiser level: This level (relative to 0.0dB which is the soundcard's clipping point) will be subtracted from all magnitudes in the frequency domain. Because white noise is equally distributed over the spectrum, the impact of this subtraction is significantly larger than on coherent signals. A good starting point is setting the denoiser level slightly above the noise level, for example -60dB. Too high values for the denoiser level (above - 40dB) cause funny sounding noises and make human voices unreadable.

Notes:

• The FFT used in these filters is not affected by the "FFT settings" for the spectrum display. The filter is an encapsulated function block which has no connection to the spectrum analyzer (unless you use some tricky programming with SpecLab's built-in interpreter).
• On a 1.7-GHz-Pentium 4, with stereo processing at 44.1 kHz sample rate, the FFT filters consume about 6 % of the CPU power. On older machines, especially the old 300 MHz AMD K6 "cripple" in the author's notebook, the FFT filter can only be run at lower audio sampling rates.
• 
  

Function of the FFT-based frequency conversion ("pitch shift")

<ToDo: a lot..> (works, but still subject to change)

Note that unlike a classic frequency converter, the FFT-based filter can only shift frequencies by multiples of an FFT bin width. The longer the FFT, the finer the stepwidth for this kind of frequency conversion.

If frequencies shall be moved DOWN, the conversion takes place as the first processing step. If frequencies shall be moved UP, it happens as last processing step. Why ? Because this way, the filter response, frequency inversion range, etc always remain at 'baseband' - regardless of the shift value. This simplifies switching from receive (=move frequency DOWN) and transmit (=move frequency UP), if the FFT-based filter is used as the core for a software-defined radio.

For convenience, the frequency shift can be connected to one of the frequency markers ("diamonds") on the main frequency scale, so you can move the marker with the mouse for tuning like in a software-defined radio. More details on this are in the chapter 'Interpreter commands for the digital filters'.

Function of the FFT-based USB / LSB conversion ("frequency inversion")

<ToDo> (works, but subject to change)

Function of the FFT-based autonotch

The autonotch in the FFT-based filter works like this :

1. Convert a block of samples from the time domain into the frequency domain, using the FFT. Let's call the result "FFT bins".
2. Calculate the powers from all FFT bins.
3. From the powers of current FFT bins, calculate "slowly average". The autonotch speed parameter is used in this step.
4. Compare the power of each (averaged) FFT bin with its neighbours. If the bin exceeds the average power of its neighbours (say 10 bins to the left and the right), set this bin in the complex spectrum (and a few bins to the left and the right, depending on the configuration) to zero.
5. Multiply the complex spectrum with the filter coefficients (like in normal mode without autonotch, for bandpass / lowpass / highpass function).
6. Convert the complex spectrum back into the time domain, using another ("inverse") FFT.

The sample blocks use a 50 percent overlap (from the previous block), and a cos^2 window, to avoid aliasing effects which would cause an ugly low-pitched clicking sound. If you have the C++ sourcefiles, you can find more details in the file FftFilter.cpp (available on request). 

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I/Q processing with the FFT-filter

The FFT-based filter can operate in I/Q-mode. I/Q means "Inphase" and "Quadrature" channel. Search the web on "I/Q signal processing", or just "quadrature signals" in the context of digital signal processing. A few notes on how to use the spectrum analyser in I/Q mode is here. Some applications of the FFT-filter in I/Q-mode are described in the chapter about image-cancelling direct conversion receivers.
Basically, the filter processes complex values in this mode. In fact, it's complex but not complicated !

The following combinations can be selected on the Options tab of the FFT filter control panel:

• I/Q input  *and* I/Q output
  In this mode, both in- and output are complex samples. The filter response covers negative and positive frequencies.
• I/Q input + real output (no I/Q output)
  The input covers negative and positive frequencies, but only positive frequencies are sent to the output (with one channel). Negative frequencies can be processed though, because the FFT-based filter allows shifting frequencies from the negative part of the spectrum into the positive part, with optional mirror for the passband. Typically used as the demodulator in a single-sideband receiver with I/Q-frontend.
• real input + I/Q output
  Typically used in single-sideband exciters. The "real input" may be from a microphone, the "I/Q output" may go to an image-rejecting modulator like this one.
  
  
• real input + real output
  This is the old, default mode without I/Q processing. The filter doesn't care for negative frequencies in this mode, so the graph only shows positive frequencies.

FFT Filter Plugins

For special applications, a plugin (in the form of a special DLL) can be loaded into the FFT filter. To do this, open the filter control panel, switch to the "FFT Filter", and open the "FFT Filter Plugin" tab. Enter the name of the plugin DLL under "Name of the FFT Filter Plugin", or click on the "Load" button to open a file selector box for the DLL plugins.

Depending on the loaded filter plugin, some additional parameters may have to be set in table (as in the example above).

To develop your own FFT filter plugin, you need a C compiler (recommended : DevCpp, which is free, and based on GNU C / MinGW). As a starting point, download the "FFT Filter Plugins" package from the author's website. It contains a simple example project written in DevCpp, and a more detailed README file explaining how to write your own filter plugin.

The filter plugin parameters can be accessed through the interpreter if necessary, using the command (or function) filter.param .

Filter Implementation

The filter algorithm in Spectrum Lab runs in real time, the input can be fed from the soundcard's ADC while the output goes to the DAC.

The implementation of a "sharp" filter on a PC under Windows makes some problems, because Windows is not a real-time operating system.

A major problem is that the CPU (Pentium etc) spends a lot of time for executing other tasks and threads. The filter algorithm described above is calculated by the main CPU (not the so-called "DSP" on the soundcard which is no real DSP at all).

Because besides calculating the filter, the CPU will do "something else" for a few hundred milliseconds. To avoid interrupted audio, a sufficiently large filter holds some thousand audio samples ready for output. The soundcard driver reads data from this buffer whenever it needs to. The following diagram show the flow of information when the audio filter is active.

Sound Input
>>>
Analog to digital converter
>>>
Audio sample input buffer #1
(hard- and software)
>>>
Windows driver routine(s)
>>>
Audio sample input buffer #2
(software)
>>>
Filter algorithm
(software)
>>>
Audio sample output buffer #1
(software)
>>>
Even more windows driver(s)
>>>
Audio sample output buffer #2
(hard- and software)
>>>
Digital to analog converter
>>>
Sound Output

Without buffering, the filter will miss a lot of samples which results in audible "thumps" etc. Sometimes the filter routine even crashes completely, creating a horrible noise in the output. The result of too much sound buffering is an annoying delay between the filter input and output (you will notice it when tuning a receiver "by ear"). See the notes on testing the filter on your PC.

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Starting and stopping the filter

After configuring the filter, you are ready to start it. But before starting the filter, you should start sampling the input (from the main window, "Start Analysis"). However, you may let the filter algorithm run without the sound input but that doesn't make much sense.

Start the filter by clicking the "Start"-Button in the filter control window. You should see an indication of the time required for a filter calculation in that window, as long as the filter is running.

To stop the filter, click the "Stop"-Button. Remember this when an IIR filter starts to oscillate and produce annoying sounds...

You may also change the filter coefficients while the filter remains running (no need to turn the filter off to change it). Just click the "Apply"-Button of the filter control window after typing new coefficients into the grid table.

If you find the new filter behaves worse than the "old" (before clicking "Apply"), click on the "Undo"-button. This will toggle between the "old" and the "new" filter settings.

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Testing the filter on your PC

To find out if the filter runs properly on your PC, try the following:

1. Select a filter which lets everything pass (for example, a low pass filter with an upper edge frequency above 16 kHz ), or switch the digital filter in SL's component window into "bypass" mode.
2. Feed a clean sine wave of about 1kHz to the soundcards input. Watch the amplitude of the input signal with a monitor scope. Listen to the soundcard output with a headphone. If the output is "clean", you may be lucky. If you hear "thumps", clicking or cracking sounds, the CPU may be too slow or some other application occupies the CPU for too long intervals. Try another sampling rate on SpecLab's Audio Settings panel.
   If you don't hear anything, check the mixer settings of the soundcard.
3. Now modify the filter so nothing should pass (for example, low-pass with upper edge frequency of zero). This will generate silence at the filters (software-) output. If you can still hear the sine wave, try to adjust the mixer settings of the soundcard until it disappears. There is some about this in this document.

If you also use Creative Lab's Audigy 2 or similar soundcards, and have the "audio bypass" problem, also read this info.

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DSP Literature

If you want to learn more about digital signal processing, there is a large amount of literature about this fascinating subject. Here are just some of my favorites..

• Steven W. Smith, "The Scientist and Engineer's Guide to Digital Signal Processing"
  This excellent book can -or at least could- be downloaded for free in PDF-format from www.dspguide.com
• Tietze / Schenk, "Halbleiterschaltungstechnik"
  A must-have for every German electronics engineer and -student, contains basic principles of digital signal processing and filter design

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Interpreter commands for the digital filters

Up to now, there is just a small list of interpreter commands to control the digital filters. The first keyword is always "filter", followed by an index for the channel (like "filter[0]" for the left and "filter[1]" for the right channel). After this, there is at least one separator followed by another keyword defining what shall happen, etc :

• filter[N].fft.fc
  read or modify the center frequency ("fc") of the FFT-based filter when running in single-bandpass or single-bandgap mode, or the edge frequency when the FFT filter runs in lowpass- or highpass mode. This command is quite useless when the FFT filter is either not active or running in "custom filter" mode. Especially in "bandpass" mode, this parameter may be important enough to connect it to one of the frequency sliders (on the main frequency scale) as described here.
• filter[N].fft.bw
  get or set the bandwidth ("bw") of the FFT-based filter when running in single-bandpass or single-bandgap mode; no effect when the FFT filter is off or running in any other mode.
• filter[N].fft.fs
  get or set the frequency shift ("fs") of the FFT-based filter. Note that the "direction" (move up or down) is *not* controlled through this function, but through one of the "option" bits.
  Tip: The preconfigured setting "SAQrcvr1.usr" is an example for the three functions mentioned above. Some sliders on the frequency scale are used to modify the most important filter parameters by moving a frequency marker with the mouse. Need to learn how to load such settings ? Follow this link !
• filter[N].fft.inv1, filter[N].fft.inv2 
  get or set the frequency inversion range of the FFT-based (both values in Hertz). This can be used to turn USB (upper side band) into LSB (lower side band) if the FFT-based filter is used as the core of a direct-conversion receiver. A typical "inversion" range would be 0 to 3000 Hz. More on this in the description of the graphic control panel for this filter. Note: the frequency-inverter must be enabled through the filter-options (see filter.fft.options).
• filter[N].fft.type
  get or set the type of the FFT-based filter. Possible values are:
  0 = custom filter
  1 = lowpass
  2 = highpass
  3 = bandpass
  4 = bandreject
• filter[N].fft.options
  get or set some "special" options for the FFT-based filter. This is a combination of the following bit-masks (high-bits=enable, low-bits=off):
  1 = denoiser (by spectral subtraction)
  2 = automatic multi-notch filter
  4 = spectral limiter
  8 = reserved for other noise-reduction algorithm
  16 = frequency-inverter enabled
  32 = reserved for future use
  64 = move frequencies UP, instead of DOWN if this bitmask is not set
  
  
• filter[N].param[I]
  reads or modifies one of the FFT filter parameters. N is the channel number, I is the parameter index (ranging from zero to 31). The meaning of these parameters depends on the loaded FFT filter plugin.
  

Note: In the current release of Spectrum Lab, there are only two filters, one for the left and one for the right audio channel. So N may only be 0(zero) or 1(one).
(Why 0..1 and not 1..2 ? Because the author always uses array indices running from "zero" to "count of elements minus one", like in the 'C' programming language). But you may let the audio from a monophone source pass through both filters by chaining both processing branches as explained in the chapter about the test circuit.

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