Method for determining a state x k of a localizing apparatus at a time t k, the state x k being a realization of a state random variable X k, the method comprising: a) receiving a first image of a scene of interest in an indoor environment, wherein the indoor environment comprises N pre-arranged landmarks having known positions in a world coordinate system, N being a natural number; b) receiving a second image of a scene of interest in the indoor environment; c) receiving a state estimate x k ^ of the localizing apparatus at the time t k; the method being characterized in that it further comprises: d) receiving positions of n currently mapped simultaneous-localization-and-mapping (SLAM) landmarks in the scene of interest, wherein a map state s k comprises at least (i) the state x k of a localizing apparatus, (ii) the positions of the n currently mapped SLAM landmarks, and (iii) the positions of the N pre-arranged landmarks; e) determining positions of M features in the first image, M being a natural number smaller than or equal to N, and determining an injective mapping estimate from the M features into the set of N pre-arranged landmarks; f) determining positions of L SLAM features in the second image, and determining m SLAM features in the L SLAM features, wherein said m SLAM features are related to the n currently mapped SLAM landmarks, and determining a SLAM injective mapping estimate from the m SLAM features into the set of the n currently mapped SLAM landmarks; g) using the determined injective mapping estimate and the determined SLAM injective mapping estimate to set up a joint observation model as part of a state-space model, wherein the joint observation model is configured to map a map state random variable S k of which the map state s k is a realization onto a joint observation random variable Z k, wherein at the time t k, an observation z k is a realization of the joint observation random variable Z k, and wherein the observation comprises the position of at least one of the M features in the first image and the position of at least one of the m SLAM features in the second image; and h) using (i) the state estimate x k ^, (ii) the joint observation model, and (iii) the observation z k, to determine the state x k of the localizing apparatus at the time t k and to update the positions of the n currently mapped SLAM landmarks. a) receiving a first image of a scene of interest in an indoor environment, wherein the indoor environment comprises N pre-arranged landmarks having known positions in a world coordinate system, N being a natural number; b) receiving a second image of a scene of interest in the indoor environment; c) receiving a state estimate x k ^ of the localizing apparatus at the time t k; the method being characterized in that it further comprises: d) receiving positions of n currently mapped simultaneous-localization-and-mapping (SLAM) landmarks in the scene of interest, wherein a map state s k comprises at least (i) the state x k of a localizing apparatus, (ii) the positions of the n currently mapped SLAM landmarks, and (iii) the positions of the N pre-arranged landmarks; e) determining positions of M features in the first image, M being a natural number smaller than or equal to N, and determining an injective mapping estimate from the M features into the set of N pre-arranged landmarks; f) determining positions of L SLAM features in the second image, and determining m SLAM features in the L SLAM features, wherein said m SLAM features are related to the n currently mapped SLAM landmarks, and determining a SLAM injective mapping estimate from the m SLAM features into the set of the n currently mapped SLAM landmarks; g) using the determined injective mapping estimate and the determined SLAM injective mapping estimate to set up a joint observation model as part of a state-space model, wherein the joint observation model is configured to map a map state random variable S k of which the map state s k is a realization onto a joint observation random variable Z k, wherein at the time t k, an observation z k is a realization of the joint observation random variable Z k, and wherein the observation comprises the position of at least one of the M features in the first image and the position of at least one of the m SLAM features in the second image; and h) using (i) the state estimate x k ^, (ii) the joint observation model, and (iii) the observation z k, to determine the state x k of the localizing apparatus at the time t k and to update the positions of the n currently mapped SLAM landmarks.