Method of defining a navigation system comprising at least: • one navigation block comprising an inertial measurement unit and at least one terrain sensor which are accompanied by error models, • at least one onboard map accompanied by its error model, the navigation system being formalized by solving the discrete-time relation: { X t + 1 = F t X t + V t Y t = h t X t + W t, where the term X t comprises at least the kinematic state of the system, the initial state X 0 containing at least the error of the initial inertial measurement unit modeled as a centered Gaussian random variable with covariance P 0; the matrix F t of the linear evolution of the state contains at least the inertial measurement unit model used; Y=(Y t,t≥0) the observation vector is formed at least of the measurements of the terrain sensor; V t and W t are each centered independent Gaussian white noise with respective positive definite covariances Q t and R t, mutually independent and independent of the initial state X 0; the term h t represents the combination of the model of the terrain sensors and of the onboard maps, the method of defining determining sets of parameters θ I and θ C respectively applicable to the inertial measurement unit and to said at least one terrain sensor, the parameters allowing the navigation system to meet target performance criteria C iobjective and to satisfy constraints, the method of defining being characterized in that it comprises at least one simulation step computing performance criteria C i via performance functionals f i ( θ I, θ C) for various pairs of parameters ( θ I, θ C) and various envisaged trajectories of the measurement unit, followed by a step of searching for the pairs of parameters allowing the system to satisfy said target performance criteria C iobjective, each performance functional being defined by a determined linear combination of the components of the kinematic state vector, and by a statistical synthesis pertaining to time spans [t 1,t 2] determined along an envisaged trajectory, said statistical synthesis being applied to the covariance matrix arising from the Cramer-Rao bound P BCR (t) computed for each instant t included in the time span [t 1,t 2] as the inverse of the matrix J t defined by the recurrence relation: J t + 1 = Γ t + Q t + F t. J t − 1. F t T − 1, in which Q t designates the covariance matrix of the state noise comprising at least the covariance of the errors of the inertial measurement unit, F t designates the model of evolution of the system comprising at least that of the inertial measurement unit, and the matrix Γ t is computed in accordance with the relation: Γ t = ∇ X t h t. X TRUE t. R t − 1. ∇ X t h t. X TRUE t T, in which h t represents the model of said at least one terrain sensor and of the onboard map, and X TRUE t designates the state of the system comprising at least the inertial errors of the platform along the envisaged trajectory, R t designates the covariance matrix of the observation noise comprising at least the errors of the onboard map and of the terrain sensor. • one navigation block comprising an inertial measurement unit and at least one terrain sensor which are accompanied by error models, • at least one onboard map accompanied by its error model,