论文部分内容阅读
In this paper,a novel method of range ambiguity resolving based on hybrid filter is proposed for high-pulse repetition frequency (HPRF) radars.By considering the discrete-valued pulse interval number (PIN) which is described as the radial range of the target divided by the maximum unambiguous range for a certain HPRF and its incremental variable as target states,the problem of range ambiguity resolving is converted to the hybrid state estimation problem.In the initial time steps,since the range measurement is ambiguous,the hybrid state initialization is achieved by utilizing multiple HPRFs based on Euclidean distance.Then,to avoid the choice of the thresholds,the hybrid model based on six-dimension state vector is made equivalent to several hybrid models based on five-dimension state vector according to the values that PIN incremental variable may take.The hybrid estimation is achieved by comparing 2-norm of the innovations obtained from several hybrid filters.Simulation results demonstrate that the proposed method can converge more rapidly than the existing multiple hypothesis method when only one HPRF has target measurement and overcome the mistake that multiple hypothesis method makes when PIN varies.
In this paper, a novel method of range ambiguity resolving based on hybrid filter is proposed for high-pulse repetition frequency (HPRF) radars.By considering the discrete-valued pulse interval number (PIN) which is described as the radial range of the target divided by the maximum unambiguous range for a certain HPRF and its incremental variable as a target state, the problem of range ambiguity resolving is converted to the hybrid state estimation problem.In the initial time steps, since the range measurement is ambiguous, the hybrid state initialization is implemented by utilizing multiple HPRFs based on Euclidean distance. Then, to avoid the choice of the thresholds, the hybrid model based on six-dimensional state vector is made equivalent to several hybrid models based on five-dimensional state vector according to the values that PIN incremental variable may take. The hybrid estimation was achieved by comparing 2-norm of the innovations obtained from several hybrid filters. Simulation results demons trate that the proposed method can converge more rapidly than the existing multiple hypothesis method when only one HPRF has target measurement and overcome the mistake that multiple hypothesis method makes when PIN varies.