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The need for increased dynamic range at the input to the radar digital signal processor has increased steadily over the last decade or so. This has been the result of lower expected radar cross sections, the need for better clutter suppression, and the desire to operate without sensitivity time control (STC) in some radar applications. The analog-to-digital converter (ADC) is the most significant bottleneck in achieving this needed dynamic range performance. In this report, an approach for improving effective dynamic range using multiple ADCs is described. The ADCs are arranged in parallel channels with different gains and the approach is referred to as a "Stacked Analog-to-Digital Convener," or "Stacked ADC," in this report. Detailed results are presented for an experimental system assembled to demonstrate and evaluate the concept.

A nonparametric procedure used in a constant false alarm rate (CFAR) radar extractor for detecting targets in a background of noise with unknown statistical properties is described. The detector is based on a generalization of the well-known two-sample sign test and thus requires a set of reference noise observations in addition to the set of observations being tested for signal presence. The detection performance against Gaussian noise is determined for a finite number of observations and asymptotically, for both nonfluctuating and pulse-to-pulse Rayleigh fluctuating target statistics. It is noted that the performance loss, as compared to the optimum parametric detector, depends critically on the number of reference noise observations available when the number of hits per target is not large. In the same case a much larger loss is also found for a pulse-to-pulse fluctuating target even though the asymptotic loss is the same as for a nonfluctuating target. A comparison is finally made with a detector based on the Mann-Whitney test, which usually is considered to be one of the better nonparametric procedures for the two-sample case.