Uncertain IMM Estimator for Multi-Sensor Target Tracking

Interacting Multiple Model (IMM) estimator can provide better performance of target tracking than mono model Kalman filter. In multi-sensor system ordinarily, availability of measurement from different sensors is stochastic, and it is difficult to construct uniform global observation vector and observation matrix appropri-ately in existing method. An IMM estimator for uncertain measurement is presented. By the method invalid measurement is regarded as outlier, and approximation is reconstructed by feedback of system state estima-tion of fusion center. Then nominally generalized certain measurement can be obtained by substituting re-constructed one for invalid one. The generalized certain measurement can be centralized to construct global measurement and provided to IMM estimator, and existing multi-sensor IMM estimation method is general-ized to uncertain environment. Theoretical analysis and simulation results show the effectiveness of the method.

Comparison of droplet distributions from fluidic and impact sprinklers

To adapt to the trend toward low-energy precision irrigation, the droplet distributions for two new prototype sprinklers, outside signal sprinkler(OS) and fluidic sprinkler(FS), were compared with impact sprinkler(IS). A laser precipitation monitor was used to measure the droplet distributions. Droplet size and velocity distributions were tested under four operating pressures for nozzles 1.5 m above the ground. For the operating pressures tested, the mean OS, FS and IS droplet diameters ranged from 0 to 3.4, 0 to 3.5, 0 to 4.0 mm, respectively.The mean OS and FS droplet velocities ranged from 0 to6.3 m$s–1, whereas IS ranged from 0 to 6.3 m$s–1. Being gas-liquid fluidic sprinklers, droplet distributions of the OS and FS were similar, although not identical. IS mostly produced a 0.5 mm larger droplet diameter and a 0.5 m$s–1greater velocity than OS and FS. A new empirical equation is proposed for determination of droplet size for OS and FS, which is sufficiently accurate and simple to use. Basic statistics for droplet size and velocity were performed on data obtained by the photographic methods. The mean droplet diameter(arithmetic, volumetric and median)decreased and the mean velocity increased in operating pressure for the three types of sprinkler.

Error-space estimate method for generalized synergic target tracking

To improve the tracking accuracy and stability of an optic-electronic target tracking system,the concept of generalized synergic target and an algorithm named error-space estimate method is presented.In this algorithm,the motion of target is described by guide data and guide errors,and then the maneuver of the target is separated into guide data and guide errors to reduce the maneuver level.Then state estimate is implemented in target state-space and error-space respectively,and the prediction data of target position are acquired by synthesizing the filtering data from target state-space according to kinematic model and the prediction data from errorspace according to guide error model.Differing from typical multi-model method,the kinematic and guide error models work concurrently rather than switch between models.Experiment results show that the performance of the algorithm is better than Kalman filter and strong tracking filter at the same maneuver level.