Track-Before-Detect (TBD) Implementation with Pre-Detection Tracking

According to user requirements, we need to implement Track-Before-Detect (TBD) with pre-detection tracking capabilities. This crucial step ensures the accuracy and reliability of our system through proper signal processing before final detection decisions. The implementation maintains originality to avoid intellectual property and copyright issues while utilizing classical algorithms for comprehensive scenario simulation. In our simulation framework, we employ proven tracking algorithms to model various operational scenarios, followed by thorough result analysis and performance evaluation. The system architecture utilizes a dual-file approach: one module generates raw sensor data while another accumulates and processes tracking metrics. This separation allows for efficient data management and real-time processing capabilities. Key implementation details include: - Integrated Constant False Alarm Rate (CFAR) detection subsystem - Multi-frame data association algorithms for track formation - Probability-based detection thresholds - Adaptive filtering techniques for noise reduction Our objective is to establish a robust TBD system that can effectively identify and process false alarm situations through continuous monitoring and adaptive threshold adjustment mechanisms.