“…For simplicity, we assume that the sensor platform is constant and therefore will adopt pure PN for guidance purposes. Using pure PN for platform guidance, we have the lateral acceleration as [19,20]:…”
Section: Sensor Platform Modelmentioning
confidence: 99%
“…Assuming that the platform is roll-stabilised, we can treat the pitch and yaw angles which define the sensors' lines-of-sight as being independent of each other. Denoting the pitch angle as 𝜃 and the yaw angle as 𝜓, we can write the lateral accelerations as [19,20]:…”
Section: Sensor Platform Modelmentioning
confidence: 99%
“…Note that the gravitational force in the pitch direction has been ignored in Equation 3 as it does not impact the error analysis [19,20]. The angular rates can be determined from the time-based simulation using:…”
Targeting systems are subject to multiple sources of error when operating in complex environments. To reduce the effect of these errors, modern targeting systems generally include both imaging and RF sensors. Data processing then provides target detection and classification information, and the detection streams are combined using a data fusion scheme to produce an optimal target location estimate with an associated latency. In this paper, the performance of a multi-sensor system in a maritime application is investigated using a mathematical simulator that has been developed to provide the system performance error analysis for different engagement scenarios and test conditions. This simulator is described together with the sources of targeting error such as image motion blur and radar glint. Additionally, the impact of flare and chaff countermeasures on the targeting performance is reviewed in terms of different types of target recognition and tracking algorithms.
“…For simplicity, we assume that the sensor platform is constant and therefore will adopt pure PN for guidance purposes. Using pure PN for platform guidance, we have the lateral acceleration as [19,20]:…”
Section: Sensor Platform Modelmentioning
confidence: 99%
“…Assuming that the platform is roll-stabilised, we can treat the pitch and yaw angles which define the sensors' lines-of-sight as being independent of each other. Denoting the pitch angle as 𝜃 and the yaw angle as 𝜓, we can write the lateral accelerations as [19,20]:…”
Section: Sensor Platform Modelmentioning
confidence: 99%
“…Note that the gravitational force in the pitch direction has been ignored in Equation 3 as it does not impact the error analysis [19,20]. The angular rates can be determined from the time-based simulation using:…”
Targeting systems are subject to multiple sources of error when operating in complex environments. To reduce the effect of these errors, modern targeting systems generally include both imaging and RF sensors. Data processing then provides target detection and classification information, and the detection streams are combined using a data fusion scheme to produce an optimal target location estimate with an associated latency. In this paper, the performance of a multi-sensor system in a maritime application is investigated using a mathematical simulator that has been developed to provide the system performance error analysis for different engagement scenarios and test conditions. This simulator is described together with the sources of targeting error such as image motion blur and radar glint. Additionally, the impact of flare and chaff countermeasures on the targeting performance is reviewed in terms of different types of target recognition and tracking algorithms.
“…Then, information on the flight path angle can also be accurately obtained under small AOA assumption. Second, it was assumed that there was no time delay in the seeker so that the parasitic effect can be ignored [37]. Finally, the autopilot is modeled as the first-order lag system with constant time delay.…”
A Tobit Kalman filter-based guidance system was proposed for expanding the capture region of missiles with a strapdown semiactive laser seeker. The characteristics of the semiactive laser seeker were analyzed, and the narrow field-of-view laser seeker model was used based on the analysis. A guidance filter was designed to utilize the saturated region of the seeker to overcome limited maneuverability arising from the narrow field-of-view range. A Tobit Kalman filter is adopted, and the prediction stage was modified so that the Tobit Kalman filter can be applied for nonlinear process models. The filter model for estimating the look angle, LOS angle, and LOS rate was formulated. The proposed guidance filter can estimate the state more robustly even if saturated measurements are given. This study showed that widening the available field-of-view range can lead to the expansion of the capture region. The impact angle control composite guidance and impact angle control guidance with bearing-only measurement were used for intercepting the target with the desired impact angle. Numerical simulations were performed to demonstrate the effectiveness of the proposed method in the saturated region of the seeker and show that the proposed method can expand the size of the capture region.
“…Additionally, [9,10], also based on Kalman filters, proposed feedback structures to model and estimate the delayed and lost measurements in the guidance systems, employing command to line-of-sight strategy. In [11], a seeker timedelay model and a filter for obtaining the look angle rate in the feedback signal loop, based on the concept of the model matching technique, were introduced. Similarly, [12] suggested a novel Kalman filter dynamic for time-delayed and noisy measurements of optical sensors, and analyzed the robustness of the delayed pointing error measurements.…”
The time delay of seekers has grown to be a serious issue for tactical missile guidance with the development of flight vehicle technologies. To address the problem, a measurement compensation system for the seeker, with lags and delays based on predictive active disturbance rejection control, is proposed. In addition, to eliminate the effects of target maneuvers to the tactical missile guidance, an adaptive finite-time convergent sliding mode guidance law, based on super-twisting algorithm, is proposed in three-dimensional missile-target engagement kinematics. Specifically, the compensation system consists of a predictive tracking structure and an active disturbance rejection control system, which could follow a virtual measurement without lags and delays. The compensation system has advantages in disturbance rejection and model inaccuracy addressing, compared with existing compensation methods for seeker measurement. As for the sliding mode guidance law design, the proposed approach is based on an improved super-twisting algorithm with fast convergent adaptive gains, which has advantages in addressing unknown but bounded target maneuvers and avoiding chattering of the classical sliding mode control. As a result, the measurement compensation system and the adaptive sliding mode guidance law is verified robust and effective under the proposed constraints by the simulation examples.
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