CAJ | 학술논문

目标跟踪是粒子滤波算法在处理非线性问题的一种典型应用，但由于在线处理能力或传输条件的限制，实际应用中往往无法对多个传感器数据同时处理。据此，给出了一种基于多传感器选优的粒子滤波算法。假设每个时刻可以处理一个测量数据，该算法先采用加权的概率密度函数来评价每个传感器获得的测量值，并用粒子滤波对概率密度函数的加权进行实时更新，基于最大熵标准来选取最优测量数据进行处理。同时，最大熵标准保证了最优似然函数分布最宽，从而缓解粒子衰竭问题。通过数值仿真实验证明，该算法可以选择最优观测数据进行处理，有效降低多传感器测量中粒子滤波在线实时处理性能的要求，也较好地缓解了粒子滤波的“衰竭”问题。
목표근종시입자려파산법재처리비선성문제적일충전형응용，단유우재선처리능력혹전수조건적한제，실제응용중왕왕무법대다개전감기수거동시처리。거차，급출료일충기우다전감기선우적입자려파산법。가설매개시각가이처리일개측량수거，해산법선채용가권적개솔밀도함수래평개매개전감기획득적측량치，병용입자려파대개솔밀도함수적가권진행실시경신，기우최대적표준래선취최우측량수거진행처리。동시，최대적표준보증료최우사연함수분포최관，종이완해입자쇠갈문제。통과수치방진실험증명，해산법가이선택최우관측수거진행처리，유효강저다전감기측량중입자려파재선실시처이성능적요구，야교호지완해료입자려파적“쇠갈”문제。
Target tracking is one of the typical applications of particle filter algorithm in deal with the nonlinear problems. But due to the limitations of on-line processing and transmitting,it may be infeasible to process the multiple sensor data at one time. A particle filter algorithm based on multisensor prepotency is presented. Suppose that only one measured data can be pro-cess in one time,the algorithm uses weighted probability density function(PDF)to estimate the obtained value in each candi-date sensors,and real-time updates the weighting of the probability density function by particle filter. The optimal measured data is selected based on the maximum entropy rule. Meanwhile,the maximum entropy ensured the optimal likelihood function is the most widely,so that the failure problem of particle can be relieved. Numerical simulation experiment shows that the algorithm can process the optimal observation data,and effectively reduce the requirement of particle filter of multisensor in on-line real-time processing. It also relieved failure problem of particle.