FMCW Radar Estimation Algorithm with High Resolution and Low Complexity Based on Reduced Search Area.

We propose a frequency-modulated continuous wave (FMCW) radar estimation algorithm with high resolution and low complexity. The fast Fourier transform (FFT)-based algorithms and multiple signal classification (MUSIC) algorithms are used as algorithms for estimating target parameters in the FMCW radar systems. FFT-based and MUSIC algorithms have tradeoff characteristics between resolution performance and complexity. While FFT-based algorithms have the advantage of very low complexity, they have the disadvantage of a low-resolution performance; that is, estimating multiple targets with similar parameters as a single target. On the other hand, subspace-based algorithms have the advantage of a high-resolution performance, but have a problem of very high complexity. In this paper, we propose an algorithm with reduced complexity, while achieving the high-resolution performance of the subspace-based algorithm by utilizing the advantages of the two algorithms; namely, the low-complexity advantage of FFT-based algorithms and the high-resolution performance of the MUSIC algorithms. The proposed algorithm first reduces the amount of data used as input to the subspace-based algorithm by using the estimation results obtained by FFT. Secondly, it significantly reduces the range of search regions considered for pseudo-spectrum calculations in the subspace-based algorithm. The simulation and experiment results show that the proposed algorithm achieves a similar performance compared with the conventional and low complexity MUSIC algorithms, despite its considerably lower complexity.

Tracklet Pair Proposal and Context Reasoning for Video Scene Graph Generation.

Video scene graph generation (ViDSGG), the creation of video scene graphs that helps in deeper and better visual scene understanding, is a challenging task. Segment-based and sliding-window based methods have been proposed to perform this task. However, they all have certain limitations. This study proposes a novel deep neural network model called VSGG-Net for video scene graph generation. The model uses a sliding window scheme to detect object tracklets of various lengths throughout the entire video. In particular, the proposed model presents a new tracklet pair proposal method that evaluates the relatedness of object tracklet pairs using a pretrained neural network and statistical information. To effectively utilize the spatio-temporal context, low-level visual context reasoning is performed using a spatio-temporal context graph and a graph neural network as well as high-level semantic context reasoning. To improve the detection performance for sparse relationships, the proposed model applies a class weighting technique that adjusts the weight of sparse relationships to a higher level. This study demonstrates the positive effect and high performance of the proposed model through experiments using the benchmark dataset VidOR and VidVRD.

Foot Gesture Recognition Using High-Compression Radar Signature Image and Deep Learning.

Recently, Doppler radar-based foot gesture recognition has attracted attention as a hands-free tool. Doppler radar-based recognition for various foot gestures is still very challenging. So far, no studies have yet dealt deeply with recognition of various foot gestures based on Doppler radar and a deep learning model. In this paper, we propose a method of foot gesture recognition using a new high-compression radar signature image and deep learning. By means of a deep learning AlexNet model, a new high-compression radar signature is created by extracting dominant features via Singular Value Decomposition (SVD) processing; four different foot gestures including kicking, swinging, sliding, and tapping are recognized. Instead of using an original radar signature, the proposed method improves the memory efficiency required for deep learning training by using a high-compression radar signature. Original and reconstructed radar images with high compression values of 90%, 95%, and 99% were applied for the deep learning AlexNet model. As experimental results, movements of all four different foot gestures and of a rolling baseball were recognized with an accuracy of approximately 98.64%. In the future, due to the radar's inherent robustness to the surrounding environment, this foot gesture recognition sensor using Doppler radar and deep learning will be widely useful in future automotive and smart home industry fields.

High-Efficiency Super-Resolution FMCW Radar Algorithm Based on FFT Estimation.

This paper proposes a high-efficiency super-resolution frequency-modulated continuous-wave (FMCW) radar algorithm based on estimation by fast Fourier transform (FFT). In FMCW radar systems, the maximum number of samples is generally determined by the maximum detectable distance. However, targets are often closer than the maximum detectable distance. In this case, even if the number of samples is reduced, the ranges of targets can be estimated without degrading the performance. Based on this property, the proposed algorithm adaptively selects the number of samples used as input to the super-resolution algorithm depends on the coarsely estimated ranges of targets using the FFT. The proposed algorithm employs the reduced samples by the estimated distance by FFT as input to the super resolution algorithm instead of the maximum number of samples set by the maximum detectable distance. By doing so, the proposed algorithm achieves the similar performance of the conventional multiple signal classification algorithm (MUSIC), which is a representative of the super resolution algorithms while the performance does not degrade. Simulation results demonstrate the feasibility and performance improvement provided by the proposed algorithm; that is, the proposed algorithm achieves average complexity reduction of 88% compared to the conventional MUSIC algorithm while achieving its similar performance. Moreover, the improvement provided by the proposed algorithm was verified in practical conditions, as evidenced by our experimental results.

Low-Complexity MUSIC-Based Direction-of-Arrival Detection Algorithm for Frequency-Modulated Continuous-Wave Vital Radar.

This paper proposes a low complexity multiple-signal-classifier (MUSIC)-based direction-of-arrival (DOA) detection algorithm for frequency-modulated continuous-wave (FMCW) vital radars. In order to reduce redundant complexity, the proposed algorithm employs characteristics of distance between adjacent arrays having trade-offs between field of view (FOV) and resolution performance. First, the proposed algorithm performs coarse DOA estimation using fast Fourier transform. On the basis of the coarse DOA estimation, the number of channels as input of the MUSIC algorithm are selected. If the estimated DOA is smaller than 30°, it implies that there is an FOV margin. Therefore, the proposed algorithm employs only half of the channels, that is, it is the same as doubling the spacing between arrays. By doing so, the proposed algorithm achieves more than 40% complexity reduction compared to the conventional MUSIC algorithm while achieving similar performance. By experiments, it is shown that the proposed algorithm despite the low complexity is enable to distinguish the adjacent DOA in a practical environment.

A Low-Complexity FMCW Surveillance Radar Algorithm Using Two Random Beat Signals.

This paper proposes a low-complexity frequency-modulated continuous wave (FMCW) surveillance radar algorithm using random dual chirps in order to overcome the blind-speed problem and reduce the computational complexity. In surveillance radar algorithm, the most widely used moving target indicator (MTI) algorithm is proposed to effectively remove clutter. However, the MTI algorithm has a so-called 'blind-speed problem' that cannot detect a target of a specific velocity. In this paper, we try to solve the blind-speed problem of MTI algorithm by randomly selecting two beat signals selected for MTI for each frame. To further reduce the redundant complexity, the proposed algorithm first performs one-dimensional fast Fourier transform (FFT) for range detection and performs multidimensional FFT only when it is determined that a target exists at each frame. The simulation results show that despite low complexity, the proposed algorithm detects moving targets well by avoiding the problem of blind speed. Furthermore, the effectiveness of the proposed algorithm was verified by performing an experiment using the FMCW radar system in a real environment.

Low-Complexity Joint Range and Doppler FMCW Radar Algorithm Based on Number of Targets.

A low-complexity joint range and Doppler frequency-modulated continuous wave (FMCW) radar algorithm based on the number of targets is proposed in this paper. This paper introduces two low-complexity FMCW radar algorithms, that is, region of interest (ROI)-based and partial discrete Fourier transform (DFT)-based algorithms. We find the low-complexity condition of each algorithm by analyzing the complexity of these algorithms. From this analysis, it is found that the number of targets is an important factor in determining complexity. Based on this result, the proposed algorithm selects a low-complexity algorithm between two algorithms depending the estimated number of targets and thus achieves lower complexity compared two low-complexity algorithms introduced. The experimental results using real FMCW radar systems show that the proposed algorithm works well in a real environment. Moreover, central process unit time and count of float pointing are shown as a measure of complexity.

Two BRM promoter polymorphisms predict poor survival in patients with hepatocellular carcinoma.

Polymorphisms in the promoter of the BRM gene, a critical subunit of the chromatin remodeling SWI/SNF complex, have previously been implicated in risk and prognosis in Caucasian-predominant lung, head and neck, esophageal, and pancreatic cancers, and in hepatocellular cancers in Asians. We investigated the role of these polymorphisms in hepatocellular carcinoma (HCC) risk and prognosis. HCC cases were recruited in a comprehensive cancer center while the matched controls were recruited from family practice units from the same catchment area. For risk analyses, unconditional logistic regression analyses were performed in HCC patients and matched healthy controls. Overall survival analyses were performed using Cox proportional hazard models, Kaplan-Meier curves, and log-rank tests. In 266 HCC cases and 536 controls, no association between either BRM promoter polymorphism (BRM-741 or BRM-1321) and risk of HCC was identified (P > 0.10 for all comparisons). There was significant worsening of overall survival as the number of variant alleles increased: BRM-741 per variant allele adjusted hazards ratio (aHR) 5.77, 95% confidence interval (CI) 2.89-11.54 and BRM-1321 per variant allele aHR 4.09, 95%CI 2.22-7.51. The effects of these two polymorphisms were at least additive, where individuals who were double homozygotes for the variant alleles had a 45-fold increase in risk of death when compared to those who were double wild-type for the two polymorphisms. Two BRM promoter polymorphisms were strongly associated with HCC prognosis but were not associated with increased HCC susceptibility. The association was strongest in double homozygotes for the allele variants.

Unraveling the Role of Order-to-Disorder Transition in Shear Thickening Suspensions.

Using high-resolution in situ small angle x-ray scattering in conjunction with oscillatory shear on highly monodisperse silica suspensions, we demonstrate that an order-to-disorder transition leads to a dynamic shear thickening in a lower stress regime than the standard steady shear thickening. We show that the order-to-disorder transition is controlled by strain, which is distinguishably different from steady shear thickening, which is a stress-related phenomenon. The appearance of this two-step shear thinning and thickening transition is also influenced by the particle size, monodispersity, and measurement conditions (i.e., oscillatory shear versus steady shear). Our results show definitively that the order-to-disorder transition-induced thickening is completely unrelated to the mechanism that drives steady shear thickening.

Characteristics of High-Intent Suicide Attempters Admitted to Emergency Departments.

BACKGROUND: The suicide rate in Korea has been the highest among the Organization for Economic Cooperation and Development countries since 2003. However, there is a lack of in-depth data regarding the characteristics of suicide attempters. Understanding the intent of suicide attempters will help improve the effectiveness of suicide prevention strategies. Therefore, to provide a resource for developing the necessary interventions, this study aimed to examine the differences in suicide-related and clinical variables according to the strength of suicidal intent. METHODS: The subjects were 328 suicide attempters admitted to emergency departments at 5 university hospitals in Daegu-Gyeongbuk province between 2011 and 2014. We used various scales to examine suicide-related and clinical variables and a structured questionnaire to explore psychosocial characteristics. We evaluated suicidal intent using the Pierce Suicide Intent Scale and a clinician-rated scale that measured suicidal authenticity. RESULTS: Individuals with high suicidal intent were significantly older, had higher Hamilton Depression Rating Scale (HDRS) scores, higher rates of premeditation, and sustained suicidal ideation. Furthermore, suicide methods, timing, and psychiatric treatment histories differed by the strength of subjects' suicidal intent. Moreover, multiple logistic regression showed that depressed mood as a reason for attempting suicide, premeditation, and higher HDRS scores were significantly associated with higher suicidal intent. CONCLUSION: Depression, premeditation, older age, and sustained suicidal ideation were characteristics of individuals with high suicidal intent, and it is necessary to evaluate and monitor these factors to prevent repeated suicide attempts.

A Novel DFT-Based DOA Estimation by a Virtual Array Extension Using Simple Multiplications for FMCW Radar.

We propose a novel discrete Fourier transform (DFT)-based direction of arrival (DOA) estimation by a virtual array extension using simple multiplications for frequency modulated continuous wave (FMCW) radar. DFT-based DOA estimation is usually employed in radar systems because it provides the advantage of low complexity for real-time signal processing. In order to enhance the resolution of DOA estimation or to decrease the missing detection probability, it is essential to have a considerable number of channel signals. However, due to constraints of space and cost, it is not easy to increase the number of channel signals. In order to address this issue, we increase the number of effective channel signals by generating virtual channel signals using simple multiplications of the given channel signals. The increase in channel signals allows the proposed scheme to detect DOA more accurately than the conventional scheme while using the same number of channel signals. Simulation results show that the proposed scheme achieves improved DOA estimation compared to the conventional DFT-based method. Furthermore, the effectiveness of the proposed scheme in a practical environment is verified through the experiment.

Comparison of the Efficacy and Safety of Aripiprazole Versus Bupropion Augmentation in Patients With Major Depressive Disorder Unresponsive to Selective Serotonin Reuptake Inhibitors: A Randomized, Prospective, Open-Label Study.

PURPOSE: The purpose of this study was to compare the efficacy and safety of aripiprazole versus bupropion augmentation in patients with major depressive disorder (MDD) unresponsive to selective serotonin reuptake inhibitors (SSRIs). METHODS: This is the first randomized, prospective, open-label, direct comparison study between aripiprazole and bupropion augmentation. Participants had at least moderately severe depressive symptoms after 4 weeks or more of SSRI treatment. A total of 103 patients were randomized to either aripiprazole (n = 56) or bupropion (n = 47) augmentation for 6 weeks. Concomitant use of psychotropic agents was prohibited. Montgomery Asberg Depression Rating Scale, 17-item Hamilton Depression Rating scale, Iowa Fatigue Scale, Drug-Induced Extrapyramidal Symptoms Scale, Psychotropic-Related Sexual Dysfunction Questionnaire scores were obtained at baseline and after 1, 2, 4, and 6 weeks of treatment. RESULTS: Overall, both treatments significantly improved depressive symptoms without causing serious adverse events. There were no significant differences in the Montgomery Asberg Depression Rating Scale, 17-item Hamilton Depression Rating scale, and Iowa Fatigue Scale scores, and response rates. However, significant differences in remission rates between the 2 groups were evident at week 6 (55.4% vs 34.0%, respectively; P = 0.031), favoring aripiprazole over bupropion. There were no significant differences in adverse sexual events, extrapyramidal symptoms, or akathisia between the 2 groups. CONCLUSIONS: The present study suggests that aripiprazole augmentation is at least comparable to bupropion augmentation in combination with SSRI in terms of efficacy and tolerability in patients with MDD. Both aripiprazole and bupropion could help reduce sexual dysfunction and fatigue in patients with MDD. Aripiprazole and bupropion may offer effective and safe augmentation strategies in patients with MDD who are unresponsive to SSRIs. Double-blinded trials are warranted to confirm the present findings.

rs7968606 polymorphism of ANKS1B is associated with improvement in the PANSS general score of schizophrenia caused by amisulpride.

A recent genome-wide pharmacogenomics study showed that the rs7968606 single-nucleotide polymorphism (SNP) of the ankyrin repeat and sterile alpha motif domain-containing protein 1B (ANKS1B) gene approached the threshold of statistical significance. The aim of this study was to determine the association between the rs7968606 SNP of ANKS1B and the treatment response to amisulpride in schizophrenia patients. In total, 154 participants were enrolled from six university hospitals in Korea. All the subjects were interviewed before and after 6 weeks of amisulpride treatment with the aid of the positive and negative syndrome scale and the clinical global impression-severity scale. Genotyping for the rs7968606 SNP of ANKS1B was performed in 101 subjects. Both the decrease (t = -2.067, p = 0.041) and improvement rate (t = -1.990, p = 0.049) in the positive and negative syndrome scale general score differed significantly between T-allele carriers and noncarriers of this polymorphism after 6 weeks of amisulpride treatment. To the best of our knowledge, this is the first genetic association study of the relationship between the rs7968606 SNP of ANKS1B and the response of schizophrenia patients to treatment with amisulpride. Future larger-scale studies involving more SNPs of ANKS1B will improve the understanding of the pharmacogenetics underlying the treatment responses to amisulpride.

The Efficacy and Safety of HA IDF Plus (with Lidocaine) Versus HA IDF (Without Lidocaine) in Nasolabial Folds Injection: A Randomized, Multicenter, Double-Blind, Split-Face Study.

BACKGROUND: Injection-related pain of dermal fillers is a consistent and bothersome problem for patients undergoing soft tissue augmentation. Reducing the pain could improve overall patient satisfaction. OBJECTIVE: The purpose of this study was to compare the pain relief, efficacy, and safety of HA IDF plus containing lidocaine with HA IDF without lidocaine during correction of nasolabial folds (NLFs). METHODS: Sixty-two subjects were enrolled in a randomized, multicenter, double-blind, split-face study of HA IDF plus and HA IDF for NLF correction. For split-face study, HA IDF plus was injected to one side of NLF, and HA IDF was injected to the other side. The first evaluation variable was the injection site pain measured using a 100-mm visual analogue scale (VAS). The second evaluation variables included the global aesthetic improvement scale, wrinkle severity rating scale, and adverse events. RESULTS: Immediately after injection, 91.94% of subjects experienced at least 10 mm decrease in VAS scores at the side injected with HA IDF plus compared with HA IDF, and the rate of subjects is statistically significant. The two fillers were not significantly different in safety profile or wrinkle correction during the follow-up visit. CONCLUSIONS: HA IDF plus significantly reduced the injection-related pain during NLFs correction compared with HA IDF without altering clinical outcomes or safety. Both HA IDF plus and HA IDF were considerably tolerated and most adverse reactions were mild and transient. LEVEL OF EVIDENCE I: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Presacral Myelolipoma: Diagnosis on Imaging With Pathologic and Clinical Correlation.

OBJECTIVE: Myelolipoma is a benign tumor composed of fatty and hematopoietic elements. Presacral myelolipoma is rare, with fewer than 40 cases reported in the English literature. It is important to make an accurate diagnosis because there are malignant diseases included in the differential diagnosis of a presacral fatty mass, particularly liposarcoma. CONCLUSION: The combination of a well-encapsulated fat-containing presacral mass, lack of coinciding hematologic disease, and uptake on sulfur colloid scintigraphy support the diagnosis of a presacral myelolipoma.

Observation of a water droplet motion by using an oxide nanowire transistor covered by a nanofiber mesh.

The motion, in particular the flow speed and dropping height, of a water droplet was observed using a tin oxide (SnO2) nanowire transistor with a polyurethane (PU) nanofiber mesh as a selective filter. The changes in the SnO2 nanowire transistor characteristics, particularly the threshold voltage and on-current, were due to the adsorbed water molecules that acted as electron donors on the surface of the oxide nanowire semiconducting channel. The role of the PU nanofiber mesh, allowing the passage of water vapor while blocking liquid water, was to restrict the direct contact between the water droplet and the oxide nanowire semiconducting channel and electrodes, which could cause abnormal transistor characteristics. The selective filtering properties of the PU nanofiber mesh could be controlled by changing the number of PU layers.

Clinical assessment of bipolar depression: validity, factor structure and psychometric properties of the Korean version of the Bipolar Depression Rating Scale (BDRS).

BACKGROUND: The Bipolar Depression Rating Scale (BDRS) is a scale for assessment of the clinical characteristics of bipolar depression. The primary aims of this study were to describe the development of the Korean version of the BDRS (K-BDRS) and to establish more firmly its psychometric properties in terms of reliability and validity. METHODS: The study included 141 patients (62 male and 79 female) who had been diagnosed with bipolar disorder, were currently experiencing symptoms of depression, and were interviewed using the K-BDRS. Other measures included the Montgomery and Asberg Depression Scale (MADRS), the 17-item Hamilton Depression Scale (HAMD), and the Young Mania Rating Scale (YMRS). Additionally, the internal consistency, concurrent validity, inter-rater reliability, and test-retest reliability of the K-BDRS were evaluated. RESULTS: The Cronbach's α-coefficient for the K-BDRS was 0.866, the K-BDRS exhibited strong correlations with the HAMD (r = 0.788) and MADRS (r = 0.877), and the mixed symptoms score of the K-BDRS was significantly correlated with the YMRS (r = 0.611). An exploratory factor analysis revealed three factors that corresponded to psychological depressive symptoms, somatic depressive symptoms, and mixed symptoms. CONCLUSIONS: The present findings suggest that the K-BDRS has good psychometric properties and is a valid and reliable tool for assessing depressive symptoms in patients with bipolar disorder.

Long-term clinical results of posterior chamber phakic intraocular lens implantation to correct myopia.

BACKGROUND: The aim of this study was to determine whether implantable collamer lens (ICL) implantation to correct myopia is an effective and safe surgical option even after long-term follow up. DESIGN: A retrospective observational study was carried out. PARTICIPANTS: A total of 281 eyes of 145 myopic patients were included in the study. METHODS: Patients underwent ICL implantation and had the follow-up period of at least 5 years (87 ± 18.9 months). MAIN OUTCOME MEASURES: Outcome measures included uncorrected and corrected distance visual acuities, refraction for the evaluation of efficacy, safety, stability and predictability, ICL vault and adverse events. RESULTS: The final mean logMAR uncorrected and corrected distance visual acuities were 0.02 ± 0.19 and -0.12 ± 0.13, respectively. The mean efficacy and safety indices were 1.04 ± 0.32 and 1.20 ± 0.26. The mean spherical equivalent decreased from -8.74 ± 2.27 diopter (D) to -0.58 ± 0.72 D, and there was high predictability with 69.8% and 87.2% having a postoperative refraction within 0.5 D and 1.0 D, respectively. The mean postoperative vault was changed from 2.53 ± 0.6 to 2.00 ± 0.7. Six (2.1%) eyes developed cataract, and the mean endothelial cell loss was 7.8 ± 8.3%. Increased intraocular pressure was found in two (0.7%) eyes that required the exchange of lenses with different sizes. CONCLUSIONS: Implantable collamer lens implantation to correct myopia was an effective and safe surgery with high predictability and stability during long-term follow up. Slight myopic shift and cataract formation related with change in vault should be further evaluated.

Current prescription pattern of maintenance treatments for bipolar patients in Korea: A focus on the transition from acute treatments.

AIMS: We examined prescription patterns in maintenance treatment for recovered bipolar patients and compared these with acute treatments. METHODS: Using retrospective methods, the bipolar patients in clinical recovery (Clinical Global Impression Bipolar Version score ≤ 2 for 6 months) after acute episode were selected. We reviewed differences between prescription patterns at remission and after a maintenance period of at least 6 months. RESULTS: A total of 340 bipolar disorder patients were selected. During the maintenance period, more than half of the patients (192, 56.5%) took a mood stabilizer (MS) + antipsychotic (AP) combination. Among the MS, valproate (149, 43.8%) was most prescribed, and lithium (98, 28.8%) was second, but as patients moved into maintenance treatment, lithium use decreased, and the use of lamotrigine (86, 25.3%) increased. Preferred AP were quetiapine (125, 36.8%), aripiprazole (67, 19.7%), risperidone (48, 14.1%), and olanzapine (39, 11.5%). The use of olanzapine in maintenance was greatly decreased compared with that during acute treatment (67, 19.7%). Most patients did not take an antidepressant (AD), but the proportion using one or more AD was increased during maintenance (17.9% to 30.3%), and bupropion (28, 8.2%) was the preferred AD. Doses were decreased in all drugs, but lamotrigine was maintained at a dose of 133.2 ± 68.5 mg/day. CONCLUSIONS: The most common prescription combination for bipolar maintenance treatment was MS + AP. The use of AP was decreased, whereas the use of AD in combination with MS and/or AP was increased. The doses of MS and AP were generally decreased during the maintenance periods, with the exception of lamotrigine.

A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar.

For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method.