We consider a problem of radio frequency (RF) signal analysis where one sensing node observes a frequency band possibly used by multiple packet based radio transmitters. Analysis of the received signal includes two steps. In the first step we use a spectrogram to perform temporal segmentation of the received nonstationary signal. This task may be formulated as a clustering problem. In the second step we compute a certain 2-D slice of the fourth order spectrum for each of the segments found in the first step. These fourth order spectrum slices are arraigned in a three-way array. One aspect of the second step is to use uniqueness properties of the low rank decomposition of the three-way array to recover spectra and associated activity sequences of individual components in the received signal. We derive a numerical algorithm for the low rank decomposition, which computes estimates of the spectra and activity sequences by optimizing certain weighted least squares criterion under application specific constraints. Certain embodiments are illustrated with simulation examples involving signals used in 802.11a/b/g and Bluetooth networks. The disclosed methods and related systems can be used as spectrum analysis tools, providing crucial information needed for achieving efficient utilization of radio spectrum and elimination of mutual interference between the coexisting systems.