Recently, interrupted sampling repeater jamming (ISRJ) based on digital radio frequency memory (DRFM), which could easily form high-power false targets, has severely impacted radar detection capabilities. Conventional anti-ISRJ techniques ignore the operating characteristics of the jammer. Once the anti-ISRJ algorithm and the features of the jammer are mismatched, undesirable jamming residues or signal loss appear. In order to avoid these unwanted performance losses, an algorithm jointing the jam perception and the adaptive waveform is developed in this paper. First, a bi-directional Constant False Alarm Rate (CFAR) detector is introduced to locate and estimate the jamming component in radar echo. An ISRJ feature vector is then built to reconstruct and cancel jamming components for accurate detection under ISRJ. Second, an adaptive anti-ISRJ waveform is developed based on the vector, leading the DRFM to retransmit signals orthogonal to the real detection signal. Besides, the particle swarm optimization (PSO) algorithm efficiently works out the optimal waveform parameters to improve the suppression performance. As radar switches to the adaptive anti-ISRJ waveform, long-term suppression of ISRJ is achieved without locating, estimating, and suppressing the ISRJ components in each echo. Simulated experiments demonstrate that the suggested algorithm can accurately detect radar targets under ISRJ.

In this paper, in order to reduce the probability of the radar waveform intercepted by the passive detection system, the time-bandwidth product of the radar waveform is increased, and the detection probability of the radar waveform to the target is improved. This paper tackles the holographic RF stealth radar and proposes a joint coding waveform based on the linear frequency modulation (LFM) waveform. Joint coding uses complementary codes to perform phase-coding, and combines the codewords optimized by genetic algorithm in order to perform discrete frequency-coding waveform. The joint coding waveform model is theoretically analyzed, and the ambiguity function, pulse compression and target detection probability of the joint coding waveform are obtained by numerical simulation. In addition, the complexity of the algorithm and the low probability of intercept (LPI) characteristic of the joint coding waveform are analyzed. The results show that the joint coding waveform has an approximate “pushpin” ambiguity function, ultra-low sidelobe characteristics, better RF stealth and target detection performance. Finally, it has good application prospects in the current battlefield environment.

In a wireless sensor network, the signal received by the terminal processor is usually a complex single channel hybrid chaotic signal. The engineering needs to separate the useful signal from the mixed signal to perform the next transmission analysis. Since chaotic signals are nonlinear and unpredictable, traditional blind separation algorithms cannot effectively separate chaotic signals. Aiming to correct these problems—based on the particle filter estimation algorithm—an extended Kalman particle filter algorithm (EPF) and an unscented Kalman particle filter algorithm (UPF) are proposed to solve the single channel blind separation problem of chaotic signals. Mixing chaotic signals of different intensities performs blind source separation. Using different evaluation indexes carries out the experiment and performance can be analyzed. The results show that the proposed algorithm effectively separates the mixed chaotic signals.

To detect moving weak targets in the dual function radar communication (DFRC) system of an orthogonal frequency division multiplexing (OFDM) waveform, a modified hybrid integration method is addressed in this paper. A high-speed aircraft can cause range walk (RW) and Doppler walk (DW), rendering traditional detection methods ineffective. To overcome RW and DW, this paper proposes an integration approach combining DFRC and OFDM. The proposed approach consists of two primary components: intra-frame coherent integration and hybrid multi-inter-frame integration. After the echo signal is re-fragmented into multiple subfragments, the first step involves integrating energy across fixed situations within intra-frames for each subcarrier. Subsequently, coherent integration is performed across the subfragments, followed by the application of a Radon transform (RT) to generate frames based on the properties derived from the coherent integration output. This paper provides detailed expressions and analyses for various performance metrics of our proposed method, including the communication bit error ratio (BER), responses of coherent and non-coherent outputs, and probability of detection. Simulation results demonstrate the effectiveness of our strategy.

Traditional radar systems use fixed patterns and constant electromagnetic wave transmission to illuminate targets, but they often do not effectively use prior information about targets and consume significant radar resources. Cognitive radar has emerged as a way to improve resource efficiency and address these shortcomings. A joint waveform design and resource allocation strategy for cognitive radar that incorporates target situational awareness is proposed. This method integrates the interacting multiple model algorithm and the Unscented Kalman Particle Filter to achieve target situation awareness as prior knowledge. By combining the target attitude and the frequency response function of the target radar cross section at different time points in the prior knowledge, a joint beam control and power allocation strategy is formulated and transformed into an optimization problem. In addition, a cognitive pulse‐to‐pulse frequency agile waveform design method is proposed to support multiple target tracking under complex motion models. Simulation experiments demonstrate the effectiveness of this approach in obtaining accurate target situation information, achieving beam control, and optimizing power allocation. The designed waveforms can enhance radar target detection performance and improve low probability of intercept characteristics by adjusting the pulse repetition interval. This method has significant technical value.