  We describe a method for spectral cleaning and timing calibration of short
voltage time series data from individual radio interferometer receivers. It
makes use of the phase differences in Fast Fourier Transform (FFT) spectra
across antenna pairs. For strong, localized terrestrial sources these are
stable over time, while being approximately uniform-random for a sum over many
sources or for noise. Using only milliseconds-long datasets, the method finds
the strongest interfering transmitters, a first-order solution for relative
timing calibrations, and faulty data channels. No knowledge of gain response or
quiescent noise levels of the receivers is required. With relatively small data
volumes, this approach is suitable for use in an online system monitoring setup
for interferometric arrays.
  We have applied the method to our cosmic-ray data collection, a collection of
measurements of short pulses from extensive air showers, recorded by the LOFAR
radio telescope. Per air shower, we have collected 2 ms of raw time series data
for each receiver. The spectral cleaning has a calculated optimal sensitivity
corresponding to a power signal-to-noise ratio of 0.08 (or -11 dB) in a
spectral window of 25 kHz, for 2 ms of data in 48 antennas. This is well
sufficient for our application. Timing calibration across individual antenna
pairs has been performed at 0.4 ns precision; for calibration of signal clocks
across stations of 48 antennas the precision is 0.1 ns. Monitoring differences
in timing calibration per antenna pair over the course of the period 2011 to
2015 shows a precision of 0.08 ns, which is useful for monitoring and
correcting drifts in signal path synchronizations.
  A cross-check method for timing calibration is presented, using a pulse
transmitter carried by a drone flying over the array. Timing precision is
similar, 0.3 ns.

Instrumentation and Methods for Astrophysics