In [13], a dual-satellite navigation and positioning method based on the combination of passive ranging information and a Doppler navigation system (DNS) was proposed, however, the algorithm could only complete planar navigation and positioning. For cases where only two satellites are visible, [14] proposed a positioning model that calculates the absolute position by changing the relative position. The disadvantage of this algorithm is that the anti-interference performance is poor, and it is susceptible to interference from the external environment. In [15], the authors proposed a novel user position estimation algorithm, which realized position estimation using only two satellites, however, the algorithm only considers medium earth orbit (MEO) satellites and has not been verified under the LEO constellation. Based on the measured values of the pseudorange and pseudorange rate, [16] used a Kalman filter (KF) for fusion positioning. Results of this study showed that once two satellites were tracked, the overall accuracy of the positioning system was improved, however, the algorithm is unable to meet navigation and positioning needs in harsh and challenging environments. To address navigation and positioning situations in challenging environments, [17] proposed a tightly coupled integrated navigation solution made up of an adaptive low-cost global navigation satellite system (GNSS), micro-electro-mechanical systems (MEMS) and inertial measuring units (IMU) (GNSS/MEMS-IMU), with auxiliary measurement functions, with an algorithm which requires three or more satellites to be captured in order to be implemented. The authors of [18] proposed the Marquardt algorithm with an additional Earth ellipsoid equation. Under weak GNSS signal conditions, positioning can be achieved using this method when two satellite signals are captured twice in a short period, however, the algorithm requires two captures, so real-time performance cannot be guaranteed. In [19], a single-satellite positioning scheme is proposed, based on LEO constellation clock error elimination, and detailed clock error elimination principles and methods is outlined. Thisalgorithm has high positioning accuracy and is suitable for navigation and positioning problems in extreme and challenging environments. However, the study does not give a solution for other situations where there are insufficient visible satellites. For challenging environments such as inside buildings, under metal roofs, or underground, where only inertial or contact navigation methods can be used, [20; 21; 22] outline the possibility of deploying inertial navigation in wheeled mobile platforms, six-axis aircraft and trajectory control equipment, respectively. However, inertial navigation can only be used reliably when in combination with other sensors (odometer, magnetometer). One solution to the various problems associated with the algorithms described above, is the newly proposed dual-satellite integrated navigation positioning algorithm for broadband LEO constellations, which is low-cost, robust, operates in real-time, and, as an integrated navigation system, has anti-interference abilities. It can meet real-time navigation and positioning requirements without the aid of an altimeter, continuous observation, or reliance on GNSS, and it can provide a real-time location service solution in harsh and challenging environments such as lush forests, canyons, and gullies. In Section 2, we describe the corresponding algorithm principle and process. In Section 3, we analyze the integrated navigation and communication (ICN) algorithm of the broadband LEO constellation and give the corresponding state equation, observation equation and various error models. In Section 4, we describe the simulation and qualitative and quantitative analyses conducted with our algorithm for two common alternate switching situations.