Data Driven Track Before Detect Using Artificial Neural Networks

• We present two neural network solutions for data driven track before detect applications. The detected tracks may be used to estimate good initial states for traditional trackers such as Kalman filters. We evaluate the method on different scenarios with multiple targets, non-linear trajectories, and different signal to noise ratio (SNR) values. Depending on scenario, the presented method achieves 99% detection probability on Swerling 3 and 4 targets at 5 - 13 dB SNR, with 0.04 - 0.001 false tracks per frame. The presented method is compared to a theoretically optimal detector.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Nyckelord

detection association

max channel

neural networks

radar

track before detect

weak target detection

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)