In order to improve the positioning accuracy of the traditional master-slave unmanned aerial vehicle （UAV） cooperative navigation algorithm based on range and angle measurement information， given the angle and range measurement errors of low-cost slave UAV measuring equipment， the error model of the cooperative navigation system of master-slave UAV is reconstructed. The navigation and measurement errors of the slave UAV are estimated and compensated. The state equations and measurement equations are derived， then the algorithm is implemented using Kalman filter. Simulation results show that for a slave UAV’s inertial navigation system based on a low accuracy micro electromechanical system （MEMS） with a gyro drift level of 10 （°）/h， the root mean square （RMS） of the east and the north velocity errors within 500 s are 0.25 m/s and 0.74 m/s， respectively， and the RMS of the latitude and the longitude errors are 17.10 m and 9.10 m， respectively， under single master UAV combined navigation. The speed accuracy is 3—10 times higher than that of the traditional algorithm， and the position accuracy is about 20 times higher. The positioning accuracy is close to the level of master UAV under double mater UAVs’ measurement references. The estimation accuracy of range measurement errors of the slave UAV is high， while the estimation accuracy of angle measurement errors is affected by the heading accuracy of the slave UAV itself. The estimation accuracy of angle measurement error can be further improved if heading references such as magnetic heading exist.