To address the severe acquisition ambiguity problem of Binary Offset Carrier (BOC) signals under high-order modulation—caused by dense and high-amplitude side peaks in the autocorrelation function—a joint acquisition optimization system integrating FFT mean-value preprocessing and the ASPeCT algorithm is proposed. An innovative “preprocessing-acquisition” collaborative processing framework is established. Through FFT mean-value preprocessing, this framework not only significantly reduces computational complexity but, more importantly, suppresses the dense side-peak components characteristic of high-order BOC signals from the frequency-domain perspective. This fundamentally improves the input signal quality for the ASPeCT algorithm and overcomes the inherent limitation of traditional methods, where fixed weighting coefficients struggle to adapt to the side-peak structure of high-order modulation. Simulation results show that the system achieves unambiguous acquisition of high-order signals such as BOC(14,2). In the critical signal-to-noise ratio (SNR) range from -62 dB to -5 dB, it reduces the required SNR by 2–3 dB compared to the traditional ASPeCT algorithm under the same detection probability, while improving the simultaneous capture efficiency by approximately 35%.This study systematically resolves the adaptability bottleneck of the traditional ASPeCT algorithm in acquiring high-order BOC signals and provides technical support for reliable acquisition in modern navigation systems.