1. A method of definition of a navigation system comprising: one navigation block comprising an inertial platform 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 ( 1 ) 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 platform 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 platform model used; Y=(Y t ,t≧0) the observations 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 , said noise being 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 definition determining sets of parameters {right arrow over (θ)} 1 and {right arrow over (θ)} C respectively applicable to the inertial platform 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 definition further comprising at least one simulation step computing performance criteria C i via performance functionals ƒ i ({right arrow over (θ)} I ,{right arrow over (θ)} C ) for various pairs of parameters ({right arrow over (θ)} I ,{right arrow over (θ)} C ) and various envisaged trajectories of the platform, 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 platform, F t designates the model of evolution of the system comprising at least that of the inertial platform, and the matrix Γ t is computed in accordance with the relation: Γ t =∇ 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.