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Fault detection rate (FDR) and fault isolation rate (FIR) were used for electronic equipment testability demonstration usually, but they were not fit for the current electronic test equipment characteristic. So the demonstration indexes, Fault detection coverage (FDC) and fault isolation coverage (FIC) were put forward in this paper. Hypergeometric distribution was instead of Binomial distribution to show detecting success ratio. Then maximum likelihood estimate was application in point estimation. Bayes' formula was used for interval estimation. And testability demonstration rule was put forward. At last, an example was given to approve the validity and practicability of the new method.

The traditional compressed sensing SFCWSAR (Stepped Frequency Continuous Wave Synthetic Aperture Radar) sparse reconstruction algorithm consumes a lot of computer memory and cannot compensate the range migration in the same pulse group. Based on this, this paper proposes a SFCWSAR sparse reconstruction algorithm based on an approximate observation operator. First, the algorithm replaces the accurate observation operator with the approximate observation operator, which greatly reduces the computer memory consumption while the algorithm is running and realizes the compensation of the range migration in the SFCWSAR pulse group. Furthermore, the SFCWSAR sub-band echo data under full sampling conditions are used to modify the important parameter of the Doppler center frequency of the approximate observation operator, which significantly improves the reconstruction accuracy of the scene. The SFCWSAR data show that, compared with the conventional sparse autofocus algorithm, the proposed algorithm takes less memory and can reconstruct scenes with high accuracy.

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