Method, carried out by a processing unit, for estimating a constrained zonotope enclosing a motion state of at least one mobile target, the method comprising: a) linearizing a nonlinear transition model at an element of a first constrained zonotope ( Z x ( t k -1 )) enclosing the motion state at a first moment ( t k -1 ), so as to produce a linear transition model, b) computing transition linearization errors at different elements of the first constrained zonotope ( Z x ( t k -1 )), wherein a transition linearization error at a given element of the first constrained zonotope is a difference between an output resulting from applying the nonlinear transition model to the given element and an output resulting from applying the linear transition model to the given element, c) computing a second constrained zonotope that contains all the linearization errors, d) propagating the first constrained zonotope so as to obtain an a priori constrained zonotope ( Ẑ x ( t k )) enclosing the motion state at a second moment ( t k ) after the first moment ( t k -1 ), wherein the a priori constrained zonotope ( Ẑ x ( t k )) is a linear projection of a hypercube, the hypercube being subject to at least one linear constraint, and wherein the propagation of the first constrained zonotope comprises: - applying the linear transition model to the first constrained zonotope so as to produce a third constrained zonotope, and - summing the second constrained zonotope and the third constrained zonotope, e) updating the a priori constrained zonotope ( Ẑ x ( t k )) so as to obtain an a posteriori constrained zonotope ( Z' x ( t k )) enclosing the motion state at the second moment ( t k ), wherein updating the a priori constrained zonotope comprises applying an observation model to the a priori constrained zonotope and to observation data of the mobile target acquired by at least one sensor. a) linearizing a nonlinear transition model at an element of a first constrained zonotope ( Z x ( t k -1 )) enclosing the motion state at a first moment ( t k -1 ), so as to produce a linear transition model, b) computing transition linearization errors at different elements of the first constrained zonotope ( Z x ( t k -1 )), wherein a transition linearization error at a given element of the first constrained zonotope is a difference between an output resulting from applying the nonlinear transition model to the given element and an output resulting from applying the linear transition model to the given element, c) computing a second constrained zonotope that contains all the linearization errors, d) propagating the first constrained zonotope so as to obtain an a priori constrained zonotope ( Ẑ x ( t k )) enclosing the motion state at a second moment ( t k ) after the first moment ( t k -1 ), wherein the a priori constrained zonotope ( Ẑ x ( t k )) is a linear projection of a hypercube, the hypercube being subject to at least one linear constraint, and wherein the propagation of the first constrained zonotope comprises: - applying the linear transition model to the first constrained zonotope so as to produce a third constrained zonotope, and - summing the second constrained zonotope and the third constrained zonotope, - applying the linear transition model to the first constrained zonotope so as to produce a third constrained zonotope, and - summing the second constrained zonotope and the third constrained zonotope, e) updating the a priori constrained zonotope ( Ẑ x ( t k )) so as to obtain an a posteriori constrained zonotope ( Z' x ( t k )) enclosing the motion state at the second moment ( t k ), wherein updating the a priori constrained zonotope comprises applying an observation model to the a priori constrained zonotope and to observation data of the mobile target acquired by at least one sensor. <EOS>