Clutter and Range Ambiguity Suppression Using Diverse Pulse Train in Pulse Doppler System

Pulse Doppler (PD) systems are widely used for moving target detection, especially in scenarios with clutter. Range ambiguity, which arises from fixed parameters in waveforms, is an inherent drawback in conventional systems. By using a diverse pulse train such as a train of coherent diverse phase coded pulses, these ambiguous peaks can be suppressed effectively but at the cost of sidelobe dispersions. In this work, a novel efficient PD process is proposed to suppress range ambiguity and detect moving targets under strong clutter. Poly-phase coded pulses are employed along with optimal receiving filters, by which the dispersed sidelobes are mitigated to a great extent. Moreover, a novel clutter suppression procedure is included in the PD process, by which strong clutter can be greatly suppressed. Well-designed receiving and inverse filters are employed. Simulation examples are presented to verify the theories. Compared with conventional methods, much better detection results are obtained for both near and remote targets, especially in scenarios with strong clutter

Focus-before-detection Methods for Radar Detection of Near Space High-maneuvering Aircrafts

Recently emerging, high maneuvering near space targets have many characteristics that differ from conventional targets, like ultra-high speed, high-maneuverability, ultra-far range, low Radar Cross Section (RCS), plasma sheath, ionosphere layer pollution, and cosmic ray interference. Based on general signal modeling for near space targets of ground-based, airborne, and spaceborne radars, this paper proposes novel focus-before-detection methods with respect to a distributed radar network, multi-dimensions, multiple targets, micro motion, varied model, and non-parametric processing. The proposed FBD based methods can effectively suppress the strong ionosphere layer pollution and active jamming, as well as problems like the scaled effect of echoes, arbitrary motion, aperture fill time, sparse sub-band frequency synthesis, across range cell, across Doppler cell, and across beam width. The proposed Focus-Before-Detection (FBD) based methods can remarkably improve the signal processing performance on target detection, parameter estimation, maneuver tracking, high-resolution imaging, feature extraction, and target recognition. Additionally, they are suitable for both high maneuvering near space targets and conventional targets, and can be applied for both new-generation radars and conventional targets. Therefore, the proposed FBD based methods for high maneuvering near space target detection have both important academic research value and impact a wide variety of applications

MMSE-Based MDL Method for Accurate Source Number Estimation

Abstract—In civilian communication systems, the signature sequence of the desired signal in training phase is known to the receiver. In this letter, using the mutual information, we bridge the probability density function and minimum mean-square error (MMSE) between the observed data and training sequence of the desired signal, and then employ the MMSE to construct a minimum description length (MDL) criterion for accurate source enumeration. Numerical results demonstrate that the proposed method is superior to existing MDL methods in terms of detection performance particularly for small number of snapshots and/or source angular separation. Index Terms—Eigenvalue decomposition, minimum description length, sensor array processing, source number estimation. I