A method for determining the position P of one or more transmitter(s) in an array of moving sensors comprising at least N aerials adapted to measure space signatures or observation vectors A k, characterised in that it comprises at least the following steps: E 0: expressing the complex observation vector Ak, the dimension N of which is greater than 1, that is received on the array of sensors for an instant k using an unknown complex scalar coefficient αk and a complex vector model dependent on the position P: A k = α k. A k P + W k with k = 1,..., K, the indices of the instants of the K observation vector measurements, Ã k being a complex vector model dependent on the unknown parameter P, W k being an additive noise parameter; E 1: defining the criterion for jointly estimating values of the disturbance parameters α k and the value of the position P by using the maximum likelihood method in the presence of disturbance parameters and by minimising the corresponding quadratic criterion, ∧ α, P M ⁢ C = arg min P, α C α, P; E 2: estimating the disturbance parameter α for a given position by minimising the criterion C(α, P) relative to α, for a given position P where α = [α 1..., α k,... α K], determining, in order to obtain an estimated value for the disturbance parameter, the estimated values for each of the values k that vary from 1 to K; E 3: determining a criterion that solely depends on the position P by using the values of the estimated disturbance parameters; E 4: using the values obtained for the disturbance parameter α in the criterion C(α, P) and estimating the value of the position P by using the K measurements A k and the expected corrected measurements A' k that are computed as follows: A k ⁢ ʹ P = A k ⁢ P H ⁢ Γ k - 1. A k A k ⁢ P H ⁢ Γ k - 1. A k P ⁢ A k P with Γ k -1 being the covariance matrix of the observation vector Ak. E 0: expressing the complex observation vector Ak, the dimension N of which is greater than 1, that is received on the array of sensors for an instant k using an unknown complex scalar coefficient αk and a complex vector model dependent on the position P: A k = α k. A k P + W k with k = 1,..., K, the indices of the instants of the K observation vector measurements, Ã k being a complex vector model dependent on the unknown parameter P, W k being an additive noise parameter; E 1: defining the criterion for jointly estimating values of the disturbance parameters α k and the value of the position P by using the maximum likelihood method in the presence of disturbance parameters and by minimising the corresponding quadratic criterion, ∧ α, P M ⁢ C = arg min P, α C α, P; E 2: estimating the disturbance parameter α for a given position by minimising the criterion C(α, P) relative to α, for a given position P where α = [α 1..., α k,... α K], determining, in order to obtain an estimated value for the disturbance parameter, the estimated values for each of the values k that vary from 1 to K; E 3: determining a criterion that solely depends on the position P by using the values of the estimated disturbance parameters; E 4: using the values obtained for the disturbance parameter α in the criterion C(α, P) and estimating the value of the position P by using the K measurements A k and the expected corrected measurements A' k that are computed as follows: A k ⁢ ʹ P = A k ⁢ P H ⁢ Γ k - 1. A k A k ⁢ P H ⁢ Γ k - 1. A k P ⁢ A k P with Γ k -1 being the covariance matrix of the observation vector Ak.