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, <EOS>