If you try to estimate power spectral density using the intuitive unbiased estimator (the DFT), you are going to have a bad time. A vanilla periodogram has very high sideband leakage, which means that the energy of the signal at a single frequency will look as if it "smeared out" across neighboring frequencies. The standard solution to this is to use the so-called 'modified periodogram' where the implicit rectangular window is replaced by a different windowing function with lower sideband leakage. In general, there is a direct tradeoff between sideband power and center frequency power, and in this application, you would do well to use a different window, such as the blackman-harris, or hamming window. See [1] for more details.
In addition even the modified periodogram discussed above has asymptotically nonzero variance [2], which means no matter how many samples you take, you will still have 'noise' in your PSD estimate. If you use biased estimators of the periodogram, such as the welch-bartlett method or the blackman-tukey algorithm, you will get much better results.
In practice, none of it matter in this case. The leakage of rectangular window is ~30dB at a distance of 30 bins, and they aggregate more than 30 adjacent bins together ("re-bin"), making the leakage no more than 1 bin. To make things worse, the dynamic range of their receiver barely scrapes 40dB (peak) or 30dB (SFDR/SINR) - rendering the use of a more sophisticated window a moot point.
If the $650 pricetag for the hardware described in the post leaves a bad taste in your mouth, you can use a fifteen dollar (including shipping) SDR from China[0] for basically the same spectrum coverage and utility[1].
Hi, author here -- I agree, the BladeRF is overkill for this kind of application. But, we were done with what we needed it for and it was just sitting around our lab so we decided to use it. I did use an RTL-SDR to poke around in the lower half of UHF, though.
Also check out the HackRF One! You can look at a much wider spectrum, as well as broadcast. The thing itself is 300$, and completely open. (https://www.sparkfun.com/products/13001)
For those of you, like me, outside the US, be prepared for some interesting questions on ordering a HackRFOne (or I suspect the BladeRF or USRP or probably any other transmit-capable SDR):
Your recent SparkFun order contains 2x WRL-00705, 1x WRL-13001. This item is export controlled by the United States government. By law, we are required to gather the following information from you as the importer:
1) Do you intend to sell or send this item to anyone in any of the following countries: Cuba, Iran, North Korea, Sudan, or Syria?
2) Will this be used in any military applications?
3) Will you be the ultimate end user of this item? If no, please go to 3.a.
3.a) If you are not the end user, who will this item be sold or transferred to? Please include full name, physical address, end use and confirmation that they will not sell or transfer this item to any party in Cuba, Iran, North Korea, Sudan or Syria.
4) What is the end use of this item?
5) Where is the location where the item will be used?
Response to all five questions is necessary before we are able to ship your order.
Much narrower bandwidth though, and limited to below ~1700KHz - you can't snoop on WiFi/Bluetooth/upper-end-GSM-bands without futzing around with downconverters.
I have been interested in this stuff since I saw a presentation on SDR by the folks at Ettus Research (and their amazing SDR setup). I eventually bought a HackRF One from Greatscott Gadgets to play with and it, like the BladeRF can cover a lot of ground with a pretty wide chunk (its only 20Mhz bandwidth generally but this has not been a limitation so far). So far I've been looking at beacons and other iOT type things, and decoding the remote control to my ceiling fan (fun). Very fun stuff to look at the spectrum and see what is there.
In addition even the modified periodogram discussed above has asymptotically nonzero variance [2], which means no matter how many samples you take, you will still have 'noise' in your PSD estimate. If you use biased estimators of the periodogram, such as the welch-bartlett method or the blackman-tukey algorithm, you will get much better results.
[1] http://www.ni.com/white-paper/4844/en/
[2] http://www.mathworks.com/help/signal/ug/nonparametric-method...