The escalating demand for angular measurement precision in industrial automation and precision manufacturing has driven significant research into image-based photoelectric encoders, valued for their noncontact operation and high-resolution capabilities. In this study, we present a self-adaptive angular displacement measurement model utilizing triple image sensors to mitigate pronounced even-order harmonic errors and inadequate environmental susceptibility in conventional single/dual-sensor systems. The proposed design integrates a 120° symmetric configuration with a hybrid “mechanical calibration-algorithmic compensation-environmental adaptation” strategy, enhanced by extended Kalman filter (EKF) bias estimation and gradient descent weight optimization. Simulation and experimental results demonstrate that the triple-sensor system reduces the second harmonic component ratio from 2.1% (dual-sensor baseline) to 0.6%, achieving 71% harmonic suppression. Static repeatability improves by 65% (±1.2″ vs ±3.5″), while dynamic interpolation error decreases by 66% (±1.2″ vs ±3.5″). Environmental robustness tests reveal an 80% reduction in temperature drift coefficient (±0.5″/°C vs ±2.5″/°C) and an 8 dB enhancement in vibration noise rejection (50 dB vs 42 dB). The system maintains ±1.8″ accuracy under single-point failure. Through nanoimprinted gratings and 3D stacked packaging, a 40% reduction in system volume and a 30% lower power consumption are achieved, compared with conventional implementations. This work provides both theoretical and practical foundations for high-precision photoelectric encoder engineering.