In the process of attitude dynamic measurement for steering drilling tool, the bottom drilling tool combination interacts with the rock and the collision between the drilling string and shaft wall generates strong vibration, which leads to multi-frequency and high-amplitude noise interference in the original measurement signal, resulting in the extremely low signal-to-noise ratio of the drilling tool attitude measurement signal, or even completely annihilated in the noise. This severely affects the accuracy of attitude parameter calculation such as inclination angle. In order to solve this problem, this paper proposes an array tri-stable chaotic system detection method used for the dynamic measurement signal. Firstly, a variable-scale processing of the drilling tool measurement signals is performed on the drilling tool measurement signals, which involves reconstructing and transforming the frequency values of the characteristic signals to meet the constraints of phase transition of the tri-stable system output.Second, considering the deviation of traditional frequency detection methods caused by the random variation of the initial phase angle of drilling tool measurement signals,a frequency detection model based on the array tri-stable chaotic system is proposed, relying on the collaborative work of the different chaotic equations for driving signals, a full-phase coverage frequency detection method is realized to eliminate the influence of the initial phase angle of drilling tool measurement signals on the frequency detection results.Finally, a parameter estimation model based on another array tri-stable chaotic system is designed to synchronously estimate the amplitude and phase of the drilling tool measurement signal, and then recovers the complete drilling tool measurement signal. Simulation and real drilling data experiments show that this method can detect the signal-to-noise ratio threshold of the measured signal as low as -18 dB, and that the errors of the inclination are lower than 1°, Compared with the signal distortion problem of traditional filtering methods in extremely low SNR scenarios and the detection deviation problem of bi-stable chaotic systems due to incomplete phase coverage, this method exhibits significant advantages in both signal detection accuracy and inclination angle calculation precision.