A conventional “laser radar” can determine the distance to an object by measuring the time between the sending of a pulse of light and the receipt of a reflection of the pulse from the object. By comparing two or more distance measurements, a speed can also be established by noting the change in distance over time. Conventional laser radar applications only check for the leading edge of the reflected pulse to establish time of flight. However, if the pulse shape and amplitude are known, then additional information, such as the size, orientation, and direction of movement of the object may be deduced. Furthermore, because weak pulses will trigger a detector looking only for a leading edge at a later time than a strong pulse from a target at the same distance, knowledge of pulse amplitude can improve distance measurement precision.
One option for gathering this information is fast analog waveform sampling, which can be accomplished at a rate on the order of a few gigasamples per second (GSa/s). While this has the advantage of gathering a wealth of data which may be extensively processed and analyzed, it requires considerable computing power and storage space, and may present challenges where sub-nanosecond timing resolution is required over numerous channels. Very narrow pulses can also result in aliasing when they fall between scheduled measurements.
An alternative means of extracting data is the Time Over Threshold (TOT) approach. This method collects two data points per pulse: what time a pulse rises above a threshold, and what time it drops below again. A TOT measurement thus establishes the width of a pulse at a preselected level. Furthermore, when pulse shapes are relatively predictable, TOT techniques can give a good approximation of amplitude. Higher resolutions can be achieved by setting multiple thresholds on different channels and recording a time for each crossing. This can provide useful information about pulse amplitude, total energy, and the like even when the shape is somewhat unpredictable. A relatively small number of thresholds—as few as 4—can provide total pulse energy with an accuracy of a few percent. It has also been found that in some applications 8 thresholds (for a total of 16 data points) can provide total pulse energy at an accuracy substantially indistinguishable from analog sampling with thousands of points. With TOT, the waveform itself determines when data points are collected, eliminating aliasing.
However, TOT techniques require high time resolution to be useful. When time is measured using a system clock on an integrated circuit or microprocessor, a high clock speed is therefore advantageous. However, even very fast clocks may not offer the level of resolution desired, and merely increasing clock speed is an expensive way to increase resolution.