Signal modeling and impulse response shaping for semiconductor detectors

The output-signal models and impulse response shaping(IRS)functions of semiconductor detectors are important for establishing high-precision measurement systems.In this paper,an output-signal model for semiconductor detector systems is proposed.According to the proposed model,a multistage cascade deconvolution IRS algorithm was developed using the C-R inverse system,R-C inverse system,and differentiator system.The silicon drift detector signals acquired from the analog-to-digital converter were tested.The experimental results indicated that the shaped pulses obtained using the proposed model had no undershoot,and the average peak base width of the output shaped pulses was reduced by 36%compared with that for a simple model proposed in a previous work[1].Offline processing results indicated that compared with the traditional IRS algorithm,the average peak base width of the output shaped pulses obtained using the proposed algorithm was reduced by 11%,and the total elapsed time required for pulse shaping was reduced by 26%.The proposed algorithm avoids recursive calculation.If the sampling frequency of the digital system reaches 100 MHz,the proposed algorithm can be simplified to integer arithmetic.The proposed IRS algorithm can be applied to high-resolution energy spectrum analysis,highcounting rate energy spectrum correction,and coincidence and anti-coincidence measurements.

Gaussian shaper for nuclear pulses based on multilevel cascade convolution

For nuclear measurements,it is necessary to obtain accurate information from nuclear pulses,which should be obtained by first shaping the pulses outputted by the detectors.However,commonly used pulse-shaping algorithms have certain problems.For example,certain pulse-shaping algorithms have long dead-times in high-counting-rate environments or are difficult to achieve in digital systems.Gaussian signals are widely used in analog nuclear instruments owing to their symmetry and completeness.A Gaussian signal is usually implemented by using a multilevel S–K filter in series or in parallel.It is difficult to construct a real-time digital Gaussian filter for the complex Gaussian filtering algorithm.Based on the multilevel cascade convolution,a pulse-shaping algorithm for double exponential signals is proposed in this study,which,in addition to double exponential signals,allows more complex output signal models to be used in the new algorithm.The proposed algorithm can be used in high-counting-rate environments and has been implemented in an FPGA with fewer multipliers than those required in other traditional Gaussian pulse-shaping algorithms.The offline processing results indicated that the average peak base width of the output-shaped pulses obtained using the proposed algorithm was reduced compared with that obtained using the traditional Gaussian pulse-shaping algorithm.Experimental results also demonstrated that signal-to-noise ratios and energy resolutions were improved,particularly for pulses with a low energy.The energy resolution was improved by 0.1–0.2%while improving the counting rate.

Sidelobe suppression analysis of microwave photonic filter based on spectrum-shaped optical frequency combs

A finite impulse-response microwave photonic filter is typically achieved based on spectrum-shaped optical frequency combs and a dispersive element. We propose an analytical model to describe the amplitude responses of the sidelobes. The model shows that the sidelobe suppression ratio is limited by the spectrum structure of the optical combs. By taking Gaussian-profiled combs as an example, it is both theoretically and experimentally proved that the suppression ratio can be improved by optimizing the spectral power range, which is defined as the ratio of the maximum tap weight to the minimum tap weight.