A sensor data processing method, comprising: determining a reference sensor from at least two sensors in a terminal, and determining sampling moments of the reference sensor; monitoring input of observation data of the at least two sensors; when obtaining the observation data of any sensor K of the at least two sensors at any moment t 1, determining a sensor type of the sensor K, wherein if the sensor K corresponds to unary pose observation, the sensor K is a first type, if the sensor corresponds to binary pose observation, the sensor K is a second type; if the sensor K is a first sensor of the first type, determining, from the sampling moments of the reference sensor, a sampling moment T 1 that is closest to t 1, determining, based on a sampling interval of the first sensor and t 1, an interpolation coefficient λ 1 used when interpolation is performed at T 1, calculating, based on λ 1 and the observation data of the first sensor, first rotation data and first translation data that are of the first sensor at T 1, and calculating a first covariance matrix corresponding to the first rotation data and the first translation data; if the sensor K is a second sensor of the second type, determining (S 16), from the sampling moments of the reference sensor, two sampling moments T 2 and T 3 that are closest to t 1, determining, based on a sampling interval of the second sensor and t 1, an interpolation coefficient λ 2, used when interpolation is performed at T 2 and an interpolation coefficient λ 3 used when interpolation is performed at T 3, calculating, based on λ 2, λ 3, and the observation data of the second sensor, second rotation data and second translation data that are of the second sensor from T 2 to T 3, and calculating a second covariance matrix corresponding to the second rotation data and the second translation data; and merging rotation data, translation data, and covariance matrices that are at the sampling moments of the reference sensor comprising T 1, T 2, and T 3, to obtain pose estimates of the terminal at the sampling moments, wherein the to-be-merged rotation data comprises at least the first rotation data and the second rotation data, the to-be-merged translation data comprises at least the first translation data and the second translation data, and the to-be-merged covariance matrices comprise at least the first covariance matrix and/ the second covariance matrix. determining a reference sensor from at least two sensors in a terminal, and determining sampling moments of the reference sensor; monitoring input of observation data of the at least two sensors; when obtaining the observation data of any sensor K of the at least two sensors at any moment t 1, determining a sensor type of the sensor K, wherein if the sensor K corresponds to unary pose observation, the sensor K is a first type, if the sensor corresponds to binary pose observation, the sensor K is a second type; if the sensor K is a first sensor of the first type, determining, from the sampling moments of the reference sensor, a sampling moment T 1 that is closest to t 1, determining, based on a sampling interval of the first sensor and t 1, an interpolation coefficient λ 1 used when interpolation is performed at T 1, calculating, based on λ 1 and the observation data of the first sensor, first rotation data and first translation data that are of the first sensor at T 1, and calculating a first covariance matrix corresponding to the first rotation data and the first translation data; if the sensor K is a second sensor of the second type, determining (S 16), from the sampling moments of the reference sensor, two sampling moments T 2 and T 3 that are closest to t 1, determining, based on a sampling interval of the second sensor and t 1, an interpolation coefficient λ 2, used when interpolation is performed at T 2 and an interpolation coefficient λ 3 used when interpolation is performed at T 3, calculating, based on λ 2, λ 3, and the observation data of the second sensor, second rotation data and second translation data that are of the second sensor from T 2 to T 3, and calculating a second covariance matrix corresponding to the second rotation data and the second translation data; and merging rotation data, translation data, and covariance matrices that are at the sampling moments of the reference sensor comprising T 1, T 2, and T 3, to obtain pose estimates of the terminal at the sampling moments, wherein the to-be-merged rotation data comprises at least the first rotation data and the second rotation data, the to-be-merged translation data comprises at least the first translation data and the second translation data, and the to-be-merged covariance matrices comprise at least the first covariance matrix and/ the second covariance matrix.