Pseudo-spectrum-based multi-sensor multi-frame detection in mixed coordinates

Abstract

Multi-sensor track-before-detect (MS-TBD) can greatly enhance the weak target detection ability due to utilizing multi-frame (MF) data from multiple sensors. However, in the existing MS-TBD methods, when the resolutions of the MS are different, the target echoes obtained by the MS are arranged to the measurement space with unified resolution. This process may remove some valuable information of raw sensor data or introduce additional noise, which may lead to inadequate integration of the echo energy and degradation of the output envelope. For the sake of solving the issues mentioned above, a pseudo-spectrum (PS) method in mixed coordinates is investigated for TBD in MS systems. For each sensor, the conversion of each measurement cell's position from sensor coordinates to Cartesian coordinates is carried out and the prediction of that is conducted with an assumed velocity in Cartesian framework. Then the predicted position is converted back to global sensor coordinates, which takes one of the sensors as the origin. A PS is designed around the predicted global polar position and its samples are added to the integration frame for MF accumulation. This avoids additional spatial alignment and facilitates well-maintained target envelope, leading to effective energy integration and the improvement of estimation accuracy. The procedures of coordinate transformation and MF accumulation in multiple sensors are derived and the analysis of theoretical output SNR is provided. The effectiveness and the superiority of the proposed method is demonstrated by several simulations.