검출
타깃 검출, CFAR, 2차원 CFAR, ROC 곡선, 소나 방정식
Phased Array System Toolbox™에는 정합 필터링, 1차원 또는 2차원의 CFAR(일정 오경보율) 검출, 스트레치 처리 펄스 압축, 코히어런스 및 비 코히어런스 펄스 적분을 수행하기 위한 System object와 Simulink® 블록이 포함되어 있습니다. 유틸리티 함수를 사용하면 다양한 신호 대 잡음비(SNR) 수준 또는 오경보 확률에 대한 ROC(수신자 조작 특성) 곡선을 계산하고 시각화할 수 있습니다. 일련의 함수와 앱을 통해 레이다 방정식을 사용하여 레이다 분석을 수행할 수 있습니다. 예를 들어, 수신 SNR 또는 타깃의 최대 검출 거리를 추정할 수 있습니다. 소나 방정식에 대해서도 유사한 기능 집합이 제공됩니다. Blake 차트를 사용하면 레이다 커버리지를 시각화할 수 있습니다.
객체
phased.AlphaBetaFilter | Alpha-beta filter for object tracking |
phased.CFARDetector | Constant false alarm rate (CFAR) detector |
phased.CFARDetector2D | Two-dimensional CFAR detector |
phased.GLRTDetector | Generalized likelihood ratio detector (R2023b 이후) |
phased.LRTDetector | Likelihood ratio test detector (R2023b 이후) |
phased.MatchedFilter | Matched filter |
phased.StretchProcessor | Stretch processor for linear FM waveform |
phased.TimeVaryingGain | Time varying gain control |
블록
| 2-D CFAR Detector | Two-dimensional constant false alarm rate (CFAR) detector |
| CFAR Detector | Constant false alarm rate (CFAR) detector |
| Dechirp Mixer | Dechirping operation on input signal |
| GLRT Detector | Perform generalized likelihood ratio test detection (R2023b 이후) |
| LRT Detector | Likelihood ratio test detector (R2023b 이후) |
| Matched Filter | Matched filter |
| Pulse Integrator | Coherent or noncoherent pulse integration |
| Stretch Processor | Stretch processor for linear FM waveforms |
| Time Varying Gain | Time varying gain (TVG) control |
| Whitening Matrix | Whitening transformation of covariance matrix (R2026a 이후) |
함수
앱
| 소나 방정식 계산기 | Estimate maximum range, SNR, transmission loss and source level of a sonar system |
| 센서 배열 분석기 | Analyze beam patterns and performance characteristics of linear, planar, 3-D, and arbitrary sensor arrays |
도움말 항목
검출 및 추정
- Neyman-Pearson Hypothesis Testing
In phased-array applications, you sometimes need to decide between two competing hypotheses to determine the reality underlying the data the array receives. - Constant False-Alarm Rate (CFAR) Detectors
CFAR detectors apply the Neyman-Pearson criterion to target detection. The detectors estimate noise statistics from data. - Receiver Operating Characteristics
Receiver operating characteristic (ROC) curves describe a detector’s performance by relating probability of false alarm to probability of detection. - Matched Filtering
Matched filtering increases SNR and improves detection. - Stretch Processing
Stretch processing, also known as deramping or dechirping, is an alternative to matched filtering. - FMCW Range Estimation
FMCW range estimation dechirps the received signal, extracts beat frequencies, and computes the target range. - Range-Doppler Response
Perform range-Doppler processing and visualize range-Doppler maps.
위상 배열 규칙
- Standards and Conventions
This section introduces the concept of baseband signals and defines the local and global coordinate systems used in the toolbox. - Units of Measure and Physical Constants
Phased Array System Toolbox uses the International System of Units (SI).
소나 방정식
- Sonar Equation
The sonar equation is used in underwater signal processing to relate received signal power to transmitted signal power for one-way or two-way sound propagation. - Doppler Effect for Sound
The Doppler effect is the change in the observed frequency of a source due to the motion of either the source or receiver or both.
