In inverse synthetic aperture radar (ISAR) imaging, a target is usually regarded as consist of few strong (specular) scatterers and the distribution these sparse in imaging volume. this paper, we propose to incorporate signal recovery method 3D multiple-input multiple-output algorithm. Sequential order one negative exponential (SOONE) function, which forms homotopy between ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub>...

Sparse signal recovery algorithms can be used to improve radar imaging quality by using the sparse property of strong scatterers. Traditional inverse synthetic aperture (ISAR) mainly consider However, scatterers an ISAR target usually exhibit block or group structure. By utilizing inherent structure images, iterative reweighted lp (0 <p ≤ 1) algorithm is proposed enhance in this paper. Firstly, model established with aid basis, and mathematically converted into cost function optimization...

In order to solve the problem of high‐resolution ISAR imaging under condition finite pulses, an improved smoothed L0 norm (SL0) sparse signal reconstruction algorithm is proposed. Firstly, transformed into optimization minimum norm. Secondly, a single‐loop structure used instead two loop layers in SL0 which increases searching density variable parameter ensure recovery accuracy. Finally, compared step added solution along steepest descent gradient direction. The experimental results show...

Many traditional sparse signal recovery based ISAR imaging methods did not utilize the block scatterers information of targets.Some Bayesian learning algorithms are computational expensive.In this paper, a 2D 1 0 norms homotopy algorithm (the BL1L0 algorithm) is proposed and utilized to form image.Compared with Bayesian-based algorithms, can obtain images similar image quality, but computation speed faster.Real data experiments verify merits our algorithm.

Due to the poor model detection accuracy, easy overfitting and weak generalization in aircraft target under complex background SAR images, this thesis introduces an enhanced object algorithm, YOLOv8-GD, which is based on YOLOv8 framework. The Gather-and-Distribute (GD) machine were used enhance capability of multi-scale feature fusion improve correct prediction rate. GSConv employed backbone network, Wise-IoU (WIoU) loss function are raise accuracy refine model's generalizability....

In radar imaging, a target is usually consisted of few strong scatterers which are sparsely distributed.In this paper, an improved sparse signal recovery algorithm based on smoothed 0 l (SL0) norm method proposed to achieve high resolution ISAR imaging with limited pulse numbers.Firstly, one new function approximate the measure sparsity.Then single loop step used instead two layers in SL0 increases searching density variable parameter ensure accuracy without increasing computation amount,...

For radar imaging, a target usually has only few strong scatterers which are sparsely distributed. In this paper, we propose compressive sensing MIMO imaging algorithm based on smoothed<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:msub><mml:mrow><mml:mi>l</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>norm. An approximate hyperbolic tangent function is proposed as the smoothed to measure sparsity. A revised Newton...

Conventional sparse signal recovery algorithms for three dimensional (3D) ISAR imaging realign the received 3D signals into a long 1D to recovery. However, this method needs large amount of computational load and occupies huge memory. In paper, algorithm imging is presented. Firstly, model analyzed. Then proposed image. One negative exponential function sequence used as smoothed approach L0 norm. Then, single loop step instead two layers in (SL0) solve problem. Finally, gradient projection...

Dissolved gas analysis (DGA) of oil has become an effective means transformer incipient fault diagnosis due to its ability avoid the influence complex electromagnetic fields and noise from outside environment. However, accuracy based on DGA technology needs be improved. This paper presents genetic algorithm (GA) employed optimize random forest (RF) parameters improve diagnosis. Firstly, by comparisons different ratio selections, non-code method dissolved in is determined as input model. The...

Abstract In order to obtain high resolution inverse synthetic aperture radar (ISAR) sparse images, a block signal recovery ISAR imaging algorithm is proposed by considering the cluster characteristics of target in this paper. Firstly, model established, converted L0 norm optimization problem. Secondly, one negative exponential function sequence used as smoothed approach norm. Finally, revised step added ensure solving problem along steepest descent gradient direction and cost updated for...