Abstract: A method and apparatus for block averaging measurement data from dynamic, repeating input signals, for example, frequency modulated signals, take into account the time variability of the measurement sampling. Each block of measurement data is referenced to a synchronizing stimulus, and measurements are averaged both on the time axis and on the modulation axis. On the time axis, the time alignment for each individual measurement is placed at the center of the time interval during which the measurement was made. For each block of data acquired, the measurement blocks are averaged together in both dimensions, time (x-axis) and modulation (y-axis result being computed), using a stimulus synchronizing signal provided by the user as a time reference (time=0). The stimulus synchronizing signal should be a stable reference with respect to the modulation function being measured. For example, if frequency versus time is being measured, the reference should identify a repeating frequency reference.

Abstract: A time interval data processing circuit uses a pipelined hardware data processor to perform the conversion of incoming time stamp data into time interval results. These results can be further processed into a hardware accumulated histogram or can be compared against limits to determine if a time interval trigger condition has occurred. In the first stage of the pipeline, the processing circuit subtracts the two time stamps from the current and the previous event to determine the time interval between events being measured. The second stage checks the measurement result against minimum and maximum limits and determines which bin the measurement belongs in. The limit testing determines if the measurement fits the histogram limits and also yields the data required to perform measurement triggering on time intervals. The third stage of the pipeline increments the appropriate histogram bin in RAM. The first and third stages of the pipeline are themselves pipelined in substages.