In aeromagnetic surveys, the quality of magnetic information requires high-precision data processing and real-time assurance. Aiming at the problems that existing software compensation systems based on general-purpose processors suffer from high calculation latency and unpredictable timing on embedded platforms, making it difficult to meet the strict requirements for real-time performance and determinism of payload-constrained platforms such as unmanned aerial vehicles (UAVs), this paper proposes an FPGA hardware acceleration architecture for the Tolles-Lawson (TL) model. By performing hardware-oriented algebraic reconstruction on the TL model information row vectors, two processing architectures, namely “fully parallel pipelining” and “timedivision multiplexing,” were designed and compared on the Xilinx Artix-7 platform. Experimental results indicate that the fully parallel architecture compresses the single compensation latency to 540 ns but consumes 132 digital signal processing (DSP) slices; whereas the time-division multiplexing architecture, through floating-point unit sharing, occupies only 9 DSPs and 7273 look-up tables (LUTs), achieving over 90% DSP resource saving rate with a latency of 6.1 μs. Measured data validation based on the Cessna 208 flight platform shows that the compensation improvement ratio of the system reaches up to 14.8, and the standard deviation of magnetic interference signals decreases from 364.5 pT to 24.7 pT. Compared with software implementations on general-purpose processors, this hardware architecture improves calculation efficiency by 1-2 orders of magnitude while maintaining basically equivalent compensation precision. This design effectively solves the deployment problem of high-precision magnetic compensation algorithms on low-power hardware, realizes airborne aeromagnetic online compensation with high precision, strong real-time performance, and strong determinism, and provides a low-cost and engineering-feasible implementation scheme for aeromagnetic systems on platforms such as UAVs and light aircraft.