Method for estimating the pulsed response h(t) of a cable network by means of myopic deconvolution: a test signal s(t) being introduced at an input point of the network and being affected by distortions which are unknown a priori and which are represented by a distortion function ξ(t), and a signal y(t) being measured at an output point of the network, the input point and the output point preferably being the same, the measured signal y(t) being modelled by the following expression: y t = s t * h t * ξ t + n t where: * represents the convolution product operation and n(t) represents an additive measuring noise, characterised in that the method comprises: - a first step of initial estimation of the pulsed response h(t) by means of deconvolution of the signal y(t) with a deconvolution kernel which is equal to the test signal s(t) and which corresponds to the absence of linear distortions, that is to say, a distortion function ξ(t) which is equal to the identity: - a second step of estimating a kernel g(t) for deconvolution of the signal y(t) using the result of the initial estimation of the pulsed response h(t), the kernel g ( t) taking into account the distortions ξ(t) introduced by the network and being equal to s(t) * ξ(t): - a third step of refined estimation of h(t) by means of deconvolution of the signal y(t) using the kernel g ( t) estimated in the second step. a test signal s(t) being introduced at an input point of the network and being affected by distortions which are unknown a priori and which are represented by a distortion function ξ(t), and a signal y(t) being measured at an output point of the network, the input point and the output point preferably being the same, the measured signal y(t) being modelled by the following expression: y t = s t * h t * ξ t + n t where: * represents the convolution product operation and n(t) represents an additive measuring noise, characterised in that the method comprises: - a first step of initial estimation of the pulsed response h(t) by means of deconvolution of the signal y(t) with a deconvolution kernel which is equal to the test signal s(t) and which corresponds to the absence of linear distortions, that is to say, a distortion function ξ(t) which is equal to the identity: - a second step of estimating a kernel g(t) for deconvolution of the signal y(t) using the result of the initial estimation of the pulsed response h(t), the kernel g ( t) taking into account the distortions ξ(t) introduced by the network and being equal to s(t) * ξ(t): - a third step of refined estimation of h(t) by means of deconvolution of the signal y(t) using the kernel g ( t) estimated in the second step. * represents the convolution product operation and n(t) represents an additive measuring noise, - a first step of initial estimation of the pulsed response h(t) by means of deconvolution of the signal y(t) with a deconvolution kernel which is equal to the test signal s(t) and which corresponds to the absence of linear distortions, that is to say, a distortion function ξ(t) which is equal to the identity: - a second step of estimating a kernel g(t) for deconvolution of the signal y(t) using the result of the initial estimation of the pulsed response h(t), the kernel g ( t) taking into account the distortions ξ(t) introduced by the network and being equal to s(t) * ξ(t): - a third step of refined estimation of h(t) by means of deconvolution of the signal y(t) using the kernel g ( t) estimated in the second step.