Star sensors, the most accurate optical sensors for space attitude determination, are widely used in various applications. These sensors require high measurement accuracy and robust stellar spectral detection capabilities. However, ground calibration experiments for star sensors often encounter issues due to mismatches between simulated stellar spectra and observed stellar spectra, adversely affecting the accuracy of optical signal calibration. To address this, we propose a design method for a structurally simple spectral tunable stellar spectral simulation system. This system employs a supercontinuum laser as the illumination source and a digital micromirror for spectral modulation. We achieve multiplexing, spectral splitting, and collimation imaging based on dual grating dispersion. Compared with traditional stellar spectral simulation systems that rely on spatial light modulation devices, our system features a simpler structure, easier installation and adjustment, and avoids common aberrations such as spectral line coma and bending, thereby reducing reliance on complex spectral simulation algorithms.

We first analyze the factors affecting spectral simulation accuracy and utilize Gaussian distribution functions to represent the smallest spectral fitting units in spectral synthesis. We theoretically investigate the influence of varying half-peak widths and spectral peak intervals on simulation accuracy. Our findings indicate that, for an ideal smooth curve, the accuracy of the spectral simulation depends on the spectral peak interval ω rather than the half-peak width. Consequently, reducing the peak interval is crucial for achieving smooth spectral simulation. Based on this insight, we design a dual grating dispersion multiplexing adjustable stellar spectrum simulation system. To enhance energy utilization, we incorporate a laser shaping and beam expansion system instead of traditional slits and collimators in the splitting mechanism. Additionally, we implement a dual grating dispersion multiplexing splitting system that uses grating 1 for splitting and grating 2 for combining and collimating the separated beams. This approach eliminates the need to determine the optimal image position, simplifying system installation and adjustment.

We construct the system and conduct comparative experiments. The results demonstrate that the half-peak width of the monochromatic light output is approximately 40 nm, with a peak interval of about 4 nm. The simulation accuracy for the 2600 K color temperature spectrum is -4.9%, while the accuracies for the 7000 and 11000 K spectra are better than -4.7% and -4.2%, respectively. The system achieves a magnitude test accuracy better than ±0.031 Mv within the range of 0 to +5 Mv, with a simulation accuracy of +0.221 Mv at +6 Mv. The increase in magnitude simulation error is attributed to the limited adjustment capability of the digital micromirror device (DMD), necessitating consideration of the star color temperature curve during magnitude adjustments. In contrast, the traditional Czerny-Turner-based stellar spectral simulation system shows a simulation accuracy of -6.2% for the 2600 K spectrum, better than -5.9% for 7000 K, and better than +6.1% for 11000 K. Analysis of the simulation curves reveals that the output curve of our dual grating dispersion multiplexing spectrum adjustable stellar spectrum simulation system is smoother.

We analyze the factors influencing the accuracy of stellar spectral simulation and establish the conditions required for simulating stellar spectral information accurately. We propose a design method for a dual grating dispersion multiplexing spectrum adjustable stellar spectral simulation system that effectively simulates stellar spectra and magnitudes, fulfilling the requirements for ground optical signal calibration experiments for star sensors. Through comparative experiments, we demonstrate that our system offers high spectral and magnitude simulation accuracy, while its simple structure facilitates installation and adjustment, reducing dependence on complex spectral simulation algorithms.