In [13], a group of USVs with a leader was considered, in order to make sure USVs function under asymmetric range and bearing constraints, the control design incorporated an asymmetric barrier Lyapunov function (BLF), and a fast convergent observer was designed to estimate the velocity of the leader. A nonlinearly transformed formation error without considering input saturation was developed in [14]; collision-avoiding, connectivity-preserving and limited communication ranges were considered simultaneously, and a distributed controller using the transformed error was designed for each USV. In practice, designing a controller without considering the input saturation factor may lead closed-loop systems to instability. In [15], a basic controller base on two feedback functions was proposed, and the functions ensure the realization of the expected formation and input constraint. In [16], an output feedback controller was proposed by using additional controllers that are able to deal with the input saturation and underactuated problems simultaneously. In [17], an adaptive steering control method for uncertain ship dynamics with input constraint was designed; the method ensures the performance of the system under changing environmental conditions. In [18], uncertain strict-feedback nonlinear systems with input saturation and unknown disturbances were investigated, a dynamic surface control (DSC) combined with a backstepping method was proposed, and the effect of input saturation was approximated using a radial basis function neural network (RBFNN). The model uncertainties and environmental disturbances are an important challenge. To overcome these difficulties, a hub motion estimation algorithm was designed in [19], where sensor fusion was employed. A controller that forces a USV to track arbitrary reference trajectories was proposed in [20]; a disturbance observer was presented to estimate environmental disturbances. In [21], an adaptive fuzzy controller for USV exposed to ocean currents and time-varying sideslip angle was designed, the dynamic uncertainties and environmental disturbances could be compensated by the fuzzy logic system. A practical adaptive sliding mode controller for an USV was proposed in [22], where an RBFNN combined with minimum the learning parameter method was designed to approximate the uncertain system dynamics online. In [23], neural network (NN)-based tracking control of underactuated systems was surveyed; unknown parameters and matched and mismatched disturbances were considered, and an adaptive control scheme incorporating multi-layer NNs was proposed. In most of the above papers, the controller is designed by using the backstepping method, and Lyapunov function is used to analyze the stability of the system. In backstepping design, the computer explosion problem is universal. Tracking differentiators were used to solve the problem in [14]. Inspired by the above, in this paper we simultaneously consider model uncertainties, environmental disturbances, input saturation, collision avoidance and the limitations of communication distance. An extended state observer (ESO) is used for observing model uncertainties and environmental disturbances. A nonlinearly error transformation is provided for achieving the connectivity preservation, the collision avoidance and the distributed formation tracking. The USVs are interconnected through a directed communication network. Auxiliary variables are introduced to solve input saturation and the underactuated problem. Tracking differentiators are employed to calculating derivatives of virtual control variables. Finally, a distributed control law for each USV is constructed. The stability of the total closed-loop system is analyzed via Lyapunov theory. The main contributions of this paper are summarized as follows. First, compared with [13], unknown model dynamics and environmental disturbances are estimated by ESO, and graph theory is combined with a distributed controller, which makes the controller suitable to be readily applied to formation control.