Radar waveform design is of great importance for radar system performances and has drawn considerable attention recently. Constant modulus is an important waveform design consideration, both from the ...point of view of hardware realization and to allow for full utilization of the transmitter's power. In this paper, we consider the problem of constant-modulus waveform design for extended target detection with prior information about the extended target and clutter. At first, we propose an arbitrary-phase unimodular waveform design method via joint transmitter-receiver optimization. We exploit a semi-definite relaxation technique to transform an intractable non-convex problem into a convex problem, which can then be efficiently solved. Furthermore, quadrature phase shift keying waveform is designed, which is easier to implement than arbitrary-phase waveforms. Numerical results demonstrate the effectiveness of the proposed methods.
The high-resolution range (HRR) profile is an important target signature in many applications (e.g., automatic target recognition), and the radar HRR profiling performance is highly dependent on ...radar transmitted waveforms. In this paper, we consider the constant-modulus (CM) waveform optimization problem to improve HRR profiling performance for stationary targets. Firstly, several fundamental bounds regarding the profiling ambiguity, stability, and accuracy are derived. Further investigation reveals that the stability and accuracy of HRR profiling are unified in the white noise case. Aimed at improving the profiling stability and accuracy, we design two types of CM radar waveforms-the arbitrary-phase and QPSK waveforms-through a customized Gaussian randomization method. The performance of LFM waveforms is also discussed. Numerical experiments show that the optimized CM waveforms can dramatically enhance the profiling performance over the unoptimized ones.
The problem of radar constant-modulus (CM) waveform design for the detection of multiple targets is considered in this paper. The CM constraint is imposed from the perspective of hardware realization ...and full utilization of the transmitter's power. Two types of CM waveforms — the arbitrary-phase waveform and the quadrature phase shift keying waveform — are obtained by maximizing the minimum of the signal-to-clutter-plus-noise ratios of the various targets. Numerical results show that the designed CM waveforms perform satisfactorily, even when compared with their counterparts without constraints on the peak-to-average ratio.
A simple and effective quadrature phase shift keying (QPSK) signal design for a given correlation matrix is presented. The method exploits the correlation properties generated by memoryless nonlinear ...transformation of a Gaussian process. The correlation matrix of the designed QPSK signal is compared to the given matrix and good approximation is achieved.
For classic radars, pulse compression is an important way to improve range and velocity resolution. And phase-coded and frequency-coded signals are two important means to implement pulse compression. ...In this paper, we analyze the lower bound of delay and Doppler resolutions of radar phase-coded pulse and frequency-coded pulse. The lower bound of the delay-Doppler resolution of phase-coded waveform is obtained. Meanwhile, the delay resolution of radar frequency-coded waveform is discussed and two useful propositions are gotten. We also get an approximate result for Doppler resolution of frequency-coded waveform. At last, the paper is concluded and future works are pointed out.
Designing signal to satisfy specific correlation relationships is a frequently encountered question in the signal processing field. In this paper, we present an effective unimodular finite alphabet ...signal design method for a given correlation matrix. The constant modulus and finite phase alphabet constraints are practically motivated for the ease of signal generation. We leverage an alternating optimization scheme to transform the original NP-hard problem into two relatively simple questions, both of which benefit from closed-form solutions. The correlation matrix of the designed signal is compared to the desired correlation matrix and good approximation is achieved.
In this paper, we present the Sub-Adjacent Transformer with a novel attention mechanism for unsupervised time series anomaly detection. Unlike previous approaches that rely on all the points within ...some neighborhood for time point reconstruction, our method restricts the attention to regions not immediately adjacent to the target points, termed sub-adjacent neighborhoods. Our key observation is that owing to the rarity of anomalies, they typically exhibit more pronounced differences from their sub-adjacent neighborhoods than from their immediate vicinities. By focusing the attention on the sub-adjacent areas, we make the reconstruction of anomalies more challenging, thereby enhancing their detectability. Technically, our approach concentrates attention on the non-diagonal areas of the attention matrix by enlarging the corresponding elements in the training stage. To facilitate the implementation of the desired attention matrix pattern, we adopt linear attention because of its flexibility and adaptability. Moreover, a learnable mapping function is proposed to improve the performance of linear attention. Empirically, the Sub-Adjacent Transformer achieves state-of-the-art performance across six real-world anomaly detection benchmarks, covering diverse fields such as server monitoring, space exploration, and water treatment.
In this paper, we propose a new multi-modal task, namely audio-visual instance segmentation (AVIS), in which the goal is to identify, segment, and track individual sounding object instances in ...audible videos, simultaneously. To our knowledge, it is the first time that instance segmentation has been extended into the audio-visual domain. To better facilitate this research, we construct the first audio-visual instance segmentation benchmark (AVISeg). Specifically, AVISeg consists of 1,258 videos with an average duration of 62.6 seconds from YouTube and public audio-visual datasets, where 117 videos have been annotated by using an interactive semi-automatic labeling tool based on the Segment Anything Model (SAM). In addition, we present a simple baseline model for the AVIS task. Our new model introduces an audio branch and a cross-modal fusion module to Mask2Former to locate all sounding objects. Finally, we evaluate the proposed method using two backbones on AVISeg. We believe that AVIS will inspire the community towards a more comprehensive multi-modal understanding.
Aimed at the problem of over-high side-lobes of the matched filter response of common radar signals, we propose a new NLFM signal with ultra-low side-lobes. The new frequency modulation function is a ...Tangent function with its parameters determined experimentally. The simulation results suggest the new side-lobe level has been improved by at least 10dB. In this paper, we thoroughly analyze the main-lobe width, Doppler tolerance, the effect of the sampling rate and the compression rate of this new NLFM signal. Its ambiguity function is also plotted and analyzed. In the end, the consisting problems are discussed, too.
The high-resolution range (HRR) profile is an important performance indicator for modern radars. In this paper, we discuss the problems associated with radar HRR profiling of stationary targets, ...including the profiling ambiguity, stability, and accuracy. A HRR profiling algorithm based on the total least squares method is presented to verify the analysis results. Numerical results demonstrate the correctness of the analysis results as well as the effectiveness of the developed algorithm. The results in the paper can aid in radar waveform design to improve the radar profiling performance.
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