Why missile don’t use pursue tracking?

In the field of modern weapons, rockets are considered an example of precision and efficiency. Hitting targets with unparalleled precision requires a variety of tracking technologies designed to optimize performance. These techniques include “track tracking,” a method that focuses on continuous trajectory adjustment to intercept moving targets. However, a deeper understanding of the intricacies of missile guidance systems reveals complexities that prevent widespread use of tracking. This article explains the complexities of missile tracking, highlights alternative approaches, and discusses synergistic strategies to refine missile tracking technology.

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  • Enhancing Missile Tracking: Exploring Pursuit Tracking Technology

Missiles, the pinnacle of modern weaponry, are designed with precision and accuracy in mind. A myriad of tracking technologies are used to achieve goals with maximum efficiency. One of these tracking methods is “track tracking,” which continuously adjusts the missile’s trajectory to intercept a moving target. While this approach seems logical at first glance, it’s worth digging into the intricacies of missile guidance systems to understand why track-and-trace is not a mainstream option.

The Complexity of Pursuit Tracking

Pursuit tracking entails constant real-time adjustments to a missile’s flight path based on the target’s movements. In theory, this method seems foolproof, as it ensures that the missile remains on a collision course with the target. However, implementing this technique is far from straightforward.

1. Computational Burden: Pursuit tracking demands substantial computational power and advanced algorithms. Real-time processing of target data, constant adjustments to missile trajectory, and predicting the target’s future position require significant resources. This can lead to delays in decision-making, reducing the missile’s effectiveness in rapidly changing scenarios.

2. Evolving Trajectories: Targets, especially in military contexts, often employ evasive maneuvers to escape incoming missiles. Pursuit tracking assumes a linear trajectory, making it challenging to predict and respond to sudden changes in direction or speed. This can render the pursuit strategy ineffective against agile targets.

3. Sensing Limitations: Missile guidance systems rely on sensors to gather information about the target’s position and movement. Pursuit tracking is highly dependent on sensor accuracy and resolution. In scenarios where sensor data is compromised – due to factors like weather conditions or electronic countermeasures – pursuit tracking can falter.

4. Energy Efficiency: Missiles have limited fuel or propulsion systems that determine their range and maneuverability. Constantly adjusting the missile’s course consumes more energy, potentially decreasing its overall effective range and limiting its mission objectives.

5. Target Selection: Not all targets warrant pursuit tracking. Slower or less agile targets might be efficiently engaged using other guidance methods, such as predictive tracking or even pre-calculated intercept points.

The Alternatives And Complementary Approaches

To overcome the limitations of tracking, missile guidance systems often use a combination of tracking methods to ensure a higher probability of success. These include:

  1. Proportional Navigation: This guidance method is based on predicting the future position of the target and proportionally adjusting the trajectory of the missile. Calculations are simplified and effective for maneuvering objectives.
  2. Command Guidance: In this approach, an external operator continuously adjusts the missile’s path based on real-time targeting data received via a communications link.
  3. Homing guidance: Homing guidance methods such as radar homing and infrared homing are more suitable for certain scenarios because they focus on tracking specific target characteristics.
  4. Data fusion: Combining data from different sensors such as radar, lidar, and infrared improves overall tracking accuracy and reduces the impact of sensor limitations.

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