A method of tracking two targets (10, 12) denoted by q and r, the method comprising: for a first time-step, estimating a state of each respective target (10, 12); at a second time-step, measuring values for a state of a target (10, 12) and a value of an identity parameter for a target (10, 12); for the second time-step, estimating a state of each respective target (10, 12) using the estimated target states for the first time-step, and; updating the estimated target states for the second time-step by performing a Joint Probabilistic Data Association process using the measured state values and the identity parameter values, wherein the Joint Probabilistic Data Association process is implemented using a particle filter; the method characterised by: performing an identity management process to estimate the probability that a particular state measurement corresponds to a particular target (10, 12), wherein the identity management process comprises determining a mixing matrix M̂; and wherein determining the mixing matrix comprises: determining values for elements m̂ qr, where: m ^ qr = ∫ p q x p r x dx; p i x = p x i = x | Y for i = q, r, x i is a state of an i th target at the second time-step; and Y is a set of all state values and identity parameter values measured at time steps up to and including the second time-step; and forming the elements into matrix M̂ = [ m̂ qr]. for a first time-step, estimating a state of each respective target (10, 12); at a second time-step, measuring values for a state of a target (10, 12) and a value of an identity parameter for a target (10, 12); for the second time-step, estimating a state of each respective target (10, 12) using the estimated target states for the first time-step, and; updating the estimated target states for the second time-step by performing a Joint Probabilistic Data Association process using the measured state values and the identity parameter values, wherein the Joint Probabilistic Data Association process is implemented using a particle filter; the method characterised by: performing an identity management process to estimate the probability that a particular state measurement corresponds to a particular target (10, 12), wherein the identity management process comprises determining a mixing matrix M̂; and wherein determining the mixing matrix comprises: determining values for elements m̂ qr, where: m ^ qr = ∫ p q x p r x dx; p i x = p x i = x | Y for i = q, r, x i is a state of an i th target at the second time-step; and Y is a set of all state values and identity parameter values measured at time steps up to and including the second time-step; and forming the elements into matrix M̂ = [ m̂ qr]. performing an identity management process to estimate the probability that a particular state measurement corresponds to a particular target (10, 12), wherein the identity management process comprises determining a mixing matrix M̂; and wherein determining the mixing matrix comprises: determining values for elements m̂ qr, where: m ^ qr = ∫ p q x p r x dx; p i x = p x i = x | Y for i = q, r, x i is a state of an i th target at the second time-step; and Y is a set of all state values and identity parameter values measured at time steps up to and including the second time-step; and forming the elements into matrix M̂ = [ m̂ qr]. determining values for elements m̂ qr, where: m ^ qr = ∫ p q x p r x dx; p i x = p x i = x | Y for i = q, r, x i is a state of an i th target at the second time-step; and Y is a set of all state values and identity parameter values measured at time steps up to and including the second time-step; and x i is a state of an i th target at the second time-step; and Y is a set of all state values and identity parameter values measured at time steps up to and including the second time-step; and forming the elements into matrix M̂ = [ m̂ qr].