A novel detection method for warhead fragment targets in optical images under dynamic strong interference environments

A measurement system for the scattering characteristics of warhead fragments based on high-speed imaging systems offers advantages such as simple deployment,flexible maneuverability,and high spatiotemporal resolution,enabling the acquisition of full-process data of the fragment scattering process.However,mismatches between camera frame rates and target velocities can lead to long motion blur tails of high-speed fragment targets,resulting in low signal-to-noise ratios and rendering conventional detection algorithms ineffective in dynamic strong interference testing environments.In this study,we propose a detection framework centered on dynamic strong interference disturbance signal separation and suppression.We introduce a mixture Gaussian model constrained under a joint spatialtemporal-transform domain Dirichlet process,combined with total variation regularization to achieve disturbance signal suppression.Experimental results demonstrate that the proposed disturbance suppression method can be integrated with certain conventional motion target detection tasks,enabling adaptation to real-world data to a certain extent.Moreover,we provide a specific implementation of this process,which achieves a detection rate close to 100%with an approximate 0%false alarm rate in multiple sets of real target field test data.This research effectively advances the development of the field of damage parameter testing.

Multilevel analysis of the central-peripheral-target organ pathway:contributing to recovery after peripheral nerve injury

Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites,neglecting multilevel pathological analysis of the overall nervous system and target organs.This has led to restrictions on current therapeutic approaches.In this paper,we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective,covering the central nervous system,peripheral nervous system,and target organs.After peripheral nerve injury,the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves;changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord.The nerve will undergo axonal regeneration,activation of Schwann cells,inflammatory response,and vascular system regeneration at the injury site.Corresponding damage to target organs can occur,including skeletal muscle atrophy and sensory receptor disruption.We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury.The main current treatments are conducted passively and include physical factor rehabilitation,pharmacological treatments,cell-based therapies,and physical exercise.However,most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system-peripheral nervous system-target organ pathway.Therefore,we should further explore multilevel treatment options that produce effective,long-lasting results,perhaps requiring a combination of passive(traditional)and active(novel)treatment methods to stimulate rehabilitation at the central-peripheral-target organ levels to achieve better functional recovery.

Pyroptosis,ferroptosis,and autophagy in spinal cord injury:regulatory mechanisms and therapeutic targets

Regulated cell death is a form of cell death that is actively controlled by biomolecules.Several studies have shown that regulated cell death plays a key role after spinal cord injury.Pyroptosis and ferroptosis are newly discovered types of regulated cell deaths that have been shown to exacerbate inflammation and lead to cell death in damaged spinal cords.Autophagy,a complex form of cell death that is interconnected with various regulated cell death mechanisms,has garnered significant attention in the study of spinal cord injury.This injury triggers not only cell death but also cellular survival responses.Multiple signaling pathways play pivotal roles in influencing the processes of both deterioration and repair in spinal cord injury by regulating pyroptosis,ferroptosis,and autophagy.Therefore,this review aims to comprehensively examine the mechanisms underlying regulated cell deaths,the signaling pathways that modulate these mechanisms,and the potential therapeutic targets for spinal cord injury.Our analysis suggests that targeting the common regulatory signaling pathways of different regulated cell deaths could be a promising strategy to promote cell survival and enhance the repair of spinal cord injury.Moreover,a holistic approach that incorporates multiple regulated cell deaths and their regulatory pathways presents a promising multi-target therapeutic strategy for the management of spinal cord injury.

Targeting capabilities of engineered extracellular vesicles for the treatment of neurological diseases

Recent advances in research on extracellular vesicles have significantly enhanced their potential as therapeutic agents for neurological diseases.Owing to their therapeutic properties and ability to cross the blood–brain barrier,extracellular vesicles are recognized as promising drug delivery vehicles for various neurological conditions,including ischemic stroke,traumatic brain injury,neurodegenerative diseases,glioma,and psychosis.However,the clinical application of natural extracellular vesicles is hindered by their limited targeting ability and short clearance from the body.To address these limitations,multiple engineering strategies have been developed to enhance the targeting capabilities of extracellular vesicles,thereby enabling the delivery of therapeutic contents to specific tissues or cells.Therefore,this review aims to highlight the latest advancements in natural and targeting-engineered extracellular vesicles,exploring their applications in treating traumatic brain injury,ischemic stroke,Parkinson's disease,Alzheimer's disease,amyotrophic lateral sclerosis,glioma,and psychosis.Additionally,we summarized recent clinical trials involving extracellular vesicles and discussed the challenges and future prospects of using targeting-engineered extracellular vesicles for drug delivery in treating neurological diseases.This review offers new insights for developing highly targeted therapies in this field.

Subretinal fibrosis secondary to neovascular age-related macular degeneration:mechanisms and potential therapeutic targets

Subretinal fibrosis is the end-stage sequelae of neovascular age-related macular degeneration.It causes local damage to photoreceptors,retinal pigment epithelium,and choroidal vessels,which leads to permanent central vision loss of patients with neovascular age-related macular degeneration.The pathogenesis of subretinal fibrosis is complex,and the underlying mechanisms are largely unknown.Therefore,there are no effective treatment options.A thorough understanding of the pathogenesis of subretinal fibrosis and its related mechanisms is important to elucidate its complications and explore potential treatments.The current article reviews several aspects of subretinal fibrosis,including the current understanding on the relationship between neovascular age-related macular degeneration and subretinal fibrosis;multimodal imaging techniques for subretinal fibrosis;animal models for studying subretinal fibrosis;cellular and non-cellular constituents of subretinal fibrosis;pathophysiological mechanisms involved in subretinal fibrosis,such as aging,infiltration of macrophages,different sources of mesenchymal transition to myofibroblast,and activation of complement system and immune cells;and several key molecules and signaling pathways participating in the pathogenesis of subretinal fibrosis,such as vascular endothelial growth factor,connective tissue growth factor,fibroblast growth factor 2,platelet-derived growth factor and platelet-derived growth factor receptor-β,transforming growth factor-βsignaling pathway,Wnt signaling pathway,and the axis of heat shock protein 70-Toll-like receptors 2/4-interleukin-10.This review will improve the understanding of the pathogenesis of subretinal fibrosis,allow the discovery of molecular targets,and explore potential treatments for the management of subretinal fibrosis.

Targeted maintenance therapy for a young woman with cervical rhabdomyosarcoma:A case report and review of literature

BACKGROUND Rhabdomyosarcoma of the uterine cervix is a rare form of soft-tissue sarcoma predominantly affecting young women,with no established standard treatment protocol.CASE SUMMARY This report presents a case of a 17-year-old female patient presenting with in-termittent,non-cyclical vaginal bleeding and associated lower abdominal pain.Pelvic magnetic resonance imaging and additional examinations led to the dia-gnosis of cervical rhabdomyosarcoma.The primary treatment options for uterine cervical rhabdomyosarcoma include surgery,with or without adjuvant chemo-therapy and radiotherapy.This patient underwent surgery followed by a posto-perative chemotherapy regimen of gemcitabine combined with docetaxel and bevacizumab.After 19 months of follow-up,the patient showed no signs of re-currence and maintained good overall health.Given the rarity of cervix rhab-domyosarcoma,this case is presented to provide insights into the diagnosis and treatment of this condition.CONCLUSION This suggests that bevacizumab may demonstrate potential efficacy in the treat-ment of cervical rhabdomyosarcoma.In the future,targeted therapy is expected to play an increasingly significant role in the management of rhabdomyosarcoma.

Tankyrase 2 as a therapeutic target in non-small cell lung cancer: Implications for apoptosis and migration

This letter addresses Wang and Zhang's investigation into the role of tankyrase 2(TNKS2)as a pivotal driver of malignancy in non-small cell lung cancer(NSCLC)through mechanisms including apoptosis inhibition,enhanced cellular migration,andβ-catenin pathway activation.Their study in NSCLC cell lines demonstrates that TNKS2 overexpression stabilizesβ-catenin,subsequently triggering onco-genic gene expression and facilitating cellular migration-key attributes of meta-static potential.These insights position TNKS2 as a compelling target for therapy and a potential prognostic marker in NSCLC.Nevertheless,translating these in vitro findings to clinical practice requires validation in in vivo models.Addi-tionally,further research should investigate TNKS2 expression in patient samples and assess its implications in therapy resistance and combination treatment strategies.

Impact of setting distinct target blood glucose levels on endogenous insulin suppression and pharmacodynamics of insulin preparations

BACKGROUND Insulin therapy plays a crucial role in managing diabetes.Regulatory guidelines mandate assessing the pharmacokinetics(PK)and pharmacodynamics(PD)of new insulin formulations with euglycemic clamp techniques before entry into the market.Typically,blood glucose(BG)levels are maintained at 5%below baseline to suppress endogenous insulin secretion in healthy volunteers.However,in scenarios where BG baseline is relatively low,maintaining it at 5%below baseline can increase hypoglycemic risk.Consequently,we adjusted to maintain it at 2.5%below a baseline of<4.00 mmol/L.It remains uncertain whether this adjustment impacts endogenous insulin inhibition or the PD of study insulin.AIM To evaluate and compare the PD and C-peptide status using two different target BG setting methods.METHODS Data came from euglycemic clamp trials assessing the PK/PD of insulin aspart(IAsp)in healthy participants.Target BG was set at 2.5%below baseline for those with a basal BG of<4.00 mmol/L(group A),and at 5%below baseline for others(group B).The area under the curve(AUC)of IAsp(AUC_(IAsp,0-8 h))and GIR from 0 to 8 hours(AUCGIR,0-8 h)was used to characterize the PK and PD of IAsp,respectively.The C-peptide reduction and PK/PD of IAsp were compared between the two groups.RESULTS Out of 135 subjects,15 were assigned to group A and 120 to group B;however,group B exhibited higher basal Cpeptide(1.59±0.36 vs 1.32±0.42 ng/mL,P=0.006).Following propensity score matching to adjust for basal Cpeptide differences,71 subjects(15 in group A and 56 in group B)were analyzed.No significant differences were observed in demographics,IAsp dosage,or clamp quality.Group B showed significantly higher baseline(4.35±0.21 vs 3.91±0.09 mmol/L,P<0.001),target(4.13±0.20 vs 3.81±0.08 mmol/L,P<0.001),and clamped(4.10±0.17 vs 3.80±0.06 mmol/L,P<0.001)BG levels.Both groups exhibited comparable C-peptide suppression(32.5%±10.0%vs 35.6%±12.1%,P=0.370)and similar IAsp activity(AUCGIR,0-8 h:1433±400 vs 1440±397 mg/kg,P=0.952)under nearly equivalent IAsp exposure(AUC_(IAsp,0-8 h):566±51 vs 571±85 ng/mL×h,P=0.840).CONCLUSION Maintaining BG at 2.5%below a baseline of<4.00 mmol/L did not compromise the endogenous insulin suppression nor alter the observed pharmacodynamic effects of the study insulin.

Synergistic inhibition of colorectal cancer progression by silencing Aurora A and the targeting protein for Xklp2

BACKGROUND Unraveling the pathogenesis of colorectal cancer(CRC)can aid in developing prevention and treatment strategies.Aurora kinase A(AURKA)is a key participant in mitotic control and interacts with its co-activator,the targeting protein for Xklp2(TPX2)microtubule nucleation factor.AURKA is associated with poor clinical outcomes and high risks of CRC recurrence.AURKA/TPX2 co-overexpression in cancer may contribute to tumorigenesis.Despite its pivotal role in CRC development and progression,the action mechanism of AURKA remains unclear.Further research is needed to explore the complex interplay between AURKA and TPX2 and to develop effective targeted treatments for patients with CRC.AIM To compare effects of AURKA and TPX2 and their combined knockdown on CRC cells.METHODS We evaluated three CRC gene datasets about CRC(GSE32323,GSE25071,and GSE21510).Potential hub genes associated with CRC onset were identified using the Venn,search tool for the retrieval of interacting genes,and KOBAS platforms,with AURKA and TPX2 emerging as significant factors.Subsequently,cell models with knockdown of AURKA,TPX2,or both were constructed using SW480 and LOVO cells.Quantitative real-time polymerase chain reaction,western blotting,cell counting kit-8,cell cloning assays,flow cytometry,and Transwell assays were used.RESULTS Forty-three highly expressed genes and 39 poorly expressed genes overlapped in cancer tissues compared to controls from three datasets.In the protein-protein interaction network of highly expressed genes,AURKA was one of key genes.Its combined score with TPX2 was 0.999,and their co-expression score was 0.846.In CRC cells,knockdown of AURKA,TPX2,or both reduced cell viability and colony number,while blocking G0/G1 phase and enhancing cell apoptosis.Additionally,they were weakened cell proliferation and migration abilities.Furthermore,the expression levels of B-cell lymphoma-2-Associated X,caspase 3,and tumor protein P53,and E-cadherin increased with a decrease in B-cell lymphoma-2,N-cadherin,and vimentin proteins.These effects were amplified when both AURKA and TPX2 were concurrently downregulated.CONCLUSION Combined knockdown of AURKA and TPX2 was effective in suppressing the malignant phenotype in CRC.Coinhibition of gene expression is a potential developmental direction for CRC treatment.

Target acquisition performance in the presence of JPEG image compression

This paper presents an investigation on the effect of JPEG compression on the similarity between the target image and the background,where the similarity is further used to determine the degree of clutter in the image.Four new clutter metrics based on image quality assessment are introduced,among which the Haar wavelet-based perceptual similarity index,known as HaarPSI,provides the best target acquisition prediction results.It is shown that the similarity between the target and the background at the boundary between visually lossless and visually lossy compression does not change significantly compared to the case when an uncompressed image is used.In future work,through subjective tests,it is necessary to check whether this presence of compression at the threshold of just noticeable differences will affect the human target acquisition performance.Similarity values are compared with the results of subjective tests of the well-known target Search_2 database,where the degree of agreement between objective and subjective scores,measured through linear correlation,reached a value of 90%.

Parametric modeling and applications of target scattering centers:a review

The parametric scattering center model of radar tar-get has the advantages of simplicity,sparsity and mechanism relevant,making it widely applied in fields such as radar data compression and rapid generation,radar imaging,feature extraction and recognition.This paper summarizes and analyzes the research situation,development trend,and difficult prob-lems on scattering center(SC)parametric modeling from three aspects:parametric representation,determination method of model parameters,and application.

Treat to target in Crohn’s disease:A practical guide for clinicians

A treat-to-target(T2T)approach applies the principles of early intervention and tight disease control to optimise long-term outcomes in Crohn's disease.The Selecting Therapeutic Targets in Inflammatory Bowel Disease(STRIDE)-II guidelines specify short,intermediate,and long-term treatment goals,documenting specific treatment targets to be achieved at each of these timepoints.Scheduled appraisal of Crohn’s disease activity against pre-defined treatment targets at these timepoints remains central to determining whether current therapy should be continued or modified.Consensus treatment targets in Crohn’s disease comprise combination clinical and patient-reported outcome remission,in conjunction with biomarker normalisation and endoscopic healing.Although the STRIDE-II guidelines endorse the pursuit of endoscopic healing,clinicians must consider that this may not always be appropriate,acceptable,or achievable in all patients.This underscores the need to engage patients at the outset in an effort to personalise care and individualise treatment targets.The use of non-invasive biomarkers such as faecal calprotectin in conjunction with cross-sectional imaging techniques,particularly intestinal ultrasound,holds great promise;as do emerging treatment targets such as transmural healing.Two randomised clinical trials,namely,CALM and STARDUST,have evaluated the efficacy of a T2T approach in achieving endoscopic endpoints in patients with Crohn’s disease.Findings from these studies reflect that patient subgroups and Crohn’s disease characteristics likely to benefit most from a T2T approach,remain to be clarified.Moreover,outside of clinical trials,data pertaining to the real-world effectiveness of a T2T approach remains scare,highlighting the need for pragmatic real-world studies.Despite the obvious promise of a T2T approach,a lack of guidance to support its integration into real-world clinical practice has the potential to limit its uptake.This highlights the need to describe strategies,processes,and models of care capable of supporting the integration and execution of a T2T approach in real-world clinical practice.Hence,this review seeks to examine the current and emerging literature to provide clinicians with practical guidance on how to incorporate the principles of T2T into routine clinical practice for the management of Crohn’s disease.

An equivalent target plate damage probability calculation mathematics model and damage evaluation method

Aiming at the requirement of damage testing and evaluation of equivalent target plate based on the explosion of intelligent ammunition, this paper proposes a novel method for damage testing and evaluation method of circumferential equivalent target plate. Leveraging the dispersion characteristics parameters of fragment, we establish a calculation model of the fragment power situation and the damage calculation model under the condition of fragment ultimate penetration equivalent target plate. The damage model of equivalent target plate involves the fragment dispersion density, the local perforation damage criterion, the tearing damage model, and the damage probability. We use the camera to obtain the image of the equivalent target plate with fragment perforation, and research the algorithm of fragment distribution position recognition and fragment perforation area calculation method on the equivalent target plate by image processing technology. Based on the obtained parameters of the breakdown position and perforation area of fragments on equivalent target plate, we apply to damage calculation model of equivalent target plate, and calculate the damage probability of each equivalent target plate, and use the combined probabilistic damage calculation method to obtain the damage evaluation results of the circumferential equivalent target plate in an intelligent ammunition explosion experiment. Through an experimental testing, we verify the feasibility and rationality of the proposed damage evaluation method by comparison, the calculation results can reflect the actual damage effect of the equivalent target plate.

Potentials of ribosomopathy gene as pharmaceutical targets for cancer treatment

Ribosomopathies encompass a spectrum of disorders arising from impaired ribosome biogenesis and reduced functionality.Mutation or dysexpression of the genes that disturb any finely regulated steps of ribosome biogenesis can result in different types of ribosomopathies in clinic,collectively known as ribosomopathy genes.Emerging data suggest that ribosomopathy patients exhibit a significantly heightened susceptibility to cancer.Abnormal ribosome biogenesis and dysregulation of some ribosomopathy genes have also been found to be intimately associated with cancer development.The correlation between ribosome biogenesis or ribosomopathy and the development of malignancies has been well established.This work aims to review the recent advances in the research of ribosomopathy genes among human cancers and meanwhile,to excavate the potential role of these genes,which have not or rarely been reported in cancer,in the disease development across cancers.We plan to establish a theoretical framework between the ribosomopathy gene and cancer development,to further facilitate the potential of these genes as diagnostic biomarker as well as pharmaceutical targets for cancer treatment.

Ghost-YOLO v8:An Attention-Guided Enhanced Small Target Detection Algorithm for Floating Litter on Water Surfaces

Addressing the challenges in detecting surface floating litter in artificial lakes,including complex environments,uneven illumination,and susceptibility to noise andweather,this paper proposes an efficient and lightweight Ghost-YOLO(You Only Look Once)v8 algorithm.The algorithmintegrates advanced attention mechanisms and a smalltarget detection head to significantly enhance detection performance and efficiency.Firstly,an SE(Squeeze-and-Excitation)mechanism is incorporated into the backbone network to fortify the extraction of resilient features and precise target localization.This mechanism models feature channel dependencies,enabling adaptive adjustment of channel importance,thereby improving recognition of floating litter targets.Secondly,a 160×160 small-target detection layer is designed in the feature fusion neck to mitigate semantic information loss due to varying target scales.This design enhances the fusion of deep and shallow semantic information,improving small target feature representation and enabling better capture and identification of tiny floating litter.Thirdly,to balance performance and efficiency,the GhostConv module replaces part of the conventional convolutions in the feature fusion neck.Additionally,a novel C2fGhost(CSPDarknet53 to 2-Stage Feature Pyramid Networks Ghost)module is introduced to further reduce network parameters.Lastly,to address the challenge of occlusion,a newloss function,WIoU(Wise Intersection over Union)v3 incorporating a flexible and non-monotonic concentration approach,is adopted to improve detection rates for surface floating litter.The outcomes of the experiments demonstrate that the Ghost-YOLO v8 model proposed in this paper performs well in the dataset Marine,significantly enhances precision and recall by 3.3 and 7.6 percentage points,respectively,in contrast with the base model,mAP@0.5 and mAP 0.5:0.95 improve by 5.3 and 4.4 percentage points and reduces the computational volume by 1.88MB,the FPS value hardly decreases,and the efficient real-time identification of floating debris on the water’s surface can be achieved costeffectively.

Target Detection Algorithm in Foggy Scenes Based on Dual Subnets

Under the influence of air humidity,dust,aerosols,etc.,in real scenes,haze presents an uneven state.In this way,the image quality and contrast will decrease.In this case,It is difficult to detect the target in the image by the universal detection network.Thus,a dual subnet based on multi-task collaborative training(DSMCT)is proposed in this paper.Firstly,in the training phase,the Gated Context Aggregation Network(GCANet)is used as the supervisory network of YOLOX to promote the extraction of clean information in foggy scenes.In the test phase,only the YOLOX branch needs to be activated to ensure the detection speed of the model.Secondly,the deformable convolution module is used to improve GCANet to enhance the model’s ability to capture details of non-homogeneous fog.Finally,the Coordinate Attention mechanism is introduced into the Vision Transformer and the backbone network of YOLOX is redesigned.In this way,the feature extraction ability of the network for deep-level information can be enhanced.The experimental results on artificial fog data set FOG_VOC and real fog data set RTTS show that the map value of DSMCT reached 86.56%and 62.39%,respectively,which was 2.27%and 4.41%higher than the current most advanced detection model.The DSMCT network has high practicality and effectiveness for target detection in real foggy scenes.

Improved Weighted Local Contrast Method for Infrared Small Target Detection

In order to address the problem of high false alarm rate and low probabilities of infrared small target detection in complex low-altitude background,an infrared small target detection method based on improved weighted local contrast is proposed in this paper.First,the ratio information between the target and local background is utilized as an enhancement factor.The local contrast is calculated by incorporating the heterogeneity between the target and local background.Then,a local product weighted method is designed based on the spatial dissimilarity between target and background to further enhance target while suppressing background.Finally,the location of target is obtained by adaptive threshold segmentation.As experimental results demonstrate,the method shows superior performance in several evaluation metrics compared with six existing algorithms on different datasets containing targets such as unmanned aerial vehicles(UAV).

SDaDCS Remote Sensing Target Detection Algorithm

In the field of remote sensing,the rapid and accurate acquisition of the category and location of airplanes has emerged as a prominent research.However,remote sensing fuzzy imaging and complex environmental interference affect airplane detection.Besides,the inconsistency in the size of remote sensing images and the low accuracy of small target detection are crucial challenges that need to be addressed.To tackle these issues,we propose a novel network SDaDCS(SAHI-data augmentation-dilation-channel and spatial attention)based on YOLOX model and the slicing aided hyper inference(SAHI)framework,a new data augmentation technique and dilation-channel and spatial(DCS)attention mechanism.Initially,we create a remote sensing dataset for airplane targets and introduce a new data augmentation technique based on the Rotate-Mixup and mixed data augmentation to enhance data diversity.The DCS attention mechanism,which comprises the dilated convolution block,channel attention and spatial attention,is designed to bolster the feature extraction and discrimination of the network.To address the challenges arised by the difficulties of detecting small targets,we integrate the YOLOX model with the SAHI framework.Experiment results show that,when compared to the original YOLOX model,the proposed SDaDCS remote sensing target detection algorithm enhances overall accuracy by 13.6%.The experimental results validate the effectiveness of the proposed algorithm.

WSN Mobile Target Tracking Based on Improved Snake-Extended Kalman Filtering Algorithm

A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively.

Multiple model PHD filter for tracking sharply maneuvering targets using recursive RANSAC based adaptive birth estimation

An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile missiles.The probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.