The examples in this section illustrate how DSP System Toolbox™ can be used in radar, communication, and biomedical
SAR  is a technique for computing high-resolution radar returns that exceed the traditional resolution limits imposed by the physical size, or aperture, of an antenna. SAR exploits antenna motion to synthesize a large "virtual" aperture, as if the physical antenna were larger than it actually is. In this example, the SAR technique is used to form a high-resolution backscatter image of a distant area using an airborne radar platform.
Use a Kalman filter to estimate an aircraft's position and velocity from noisy radar measurements.
Model a dual-tone multifrequency (DTMF) generator and receiver. The model includes a bandpass filter bank receiver, a spectrum analyzer block showing a spectrum and spectrogram plot of the generated tones, a shift register to store the decoded digits, and a real-time soundcard audio on all platforms.
An implementation of a digital receiver that synchronizes to the time code information broadcast by radio station WWV and decodes it to display time information. The example uses the Simulink®, DSP System Toolbox™, and Stateflow® products with the MATLAB® Function block to achieve a simple noncoherent digital receiver.
Implements the Internet Low Bitrate Codec (iLBC) and illustrates its use. iLBC is designed for encoding and decoding speech for transmission via VoIP (Voice Over Internet Protocol).
Use the digital up converter (DUC) and digital down converter (DDC) System objects to design a Family Radio Service (FRS) transmitter and receiver. These objects provide tools to design interpolation/decimation filters and simplify the steps required to implement the up/down conversion process. This example illustrates both MATLAB® and Simulink® implementations. The MATLAB version uses System objects for DUC and DDC, whereas the Simulink version uses blocks for DUC and DDC. In both versions, speech signal is used as an input, and the signal after transmission is played back.
Implement two common methods of envelope detection. One method uses squaring and lowpass filtering. The other uses the Hilbert transform. This example illustrates MATLAB® and Simulink® implementations.
Detect the QRS complex of electrocardiogram (ECG) signal in real-time. Model based design is used to assist in the development, testing and deployment of the algorithm.
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