Finally a person that speaks about phase, and not frequency. Useful also would be the concept of periodicity in frequency domain at PRF rate and the blind speeds. Top video, many compliments
Maybe the IF signal starting at C (see 6:20) should start with a hill pointing downwards (similar to an initial phase of π if it were a single-tone wave)?
Just a question about the formula at 12:30 We have ∆Φ = (4π * ∆d)/λ with the angular velocity defined as: ω = ∆Φ/Tc we have ω = (4π * ∆d)/(λ*Tc) with ∆d = v*Tc we have ω = (4π * v*Tc)/(λ*Tc) which simplify to: ω = (4π * v)/λ So where did that extra Tc in your formula come from?
In section How to measure the velocity (v) of an object using 2 chirps, the measure difference of phase (ω) corresponds to the motion of the object, why the phase difference is using ω to represent, should not be ΔΦ？Is here just using different symbol to represent or some conversion between ω and ΔΦ?
@@sandeeprao3753 No, it is the instantaneous frequency of the chirp at the time τ; with a Taylor series the boxed equation in 7:50 is valid if we keep the second order term. Actually, if you see the video at 8:56 it says exactly what you say, but I think that this is a simplification by the Teacher for helping us follow his train of thought. For a perfectly accurate analysis one should not rely on Taylor series either but should calculate the absolute phase of the signal taking into account the argument of the cosine of the chirp.
Hello everyone, How can obtain the intermediate frequency signal using with Matlab ? Is true method that make element wise multiplication between transmitted chirp and received chirp signal ? I want to make sure that the phase opening process is as follows, I couldn't find many resources on this subject. As a result of phase values, it emerges in the range of -π and +π due to arctangent function or arctangent modulation, but do we need a phase unwrapping process because our real phase values may be outside this range? Thanks in advance.
To obtain the intermediate frequency (IF) signal using Matlab, you can use the following steps: Generate a chirp signal with a specific frequency range and time duration using the 'chirp' function in Matlab. Transmit the generated chirp signal through a medium or channel. Receive the transmitted signal, which may have been affected by various factors such as noise, attenuation, and dispersion. Multiply the transmitted chirp signal with the received signal element-wise to obtain the IF signal. Apply a bandpass filter to the IF signal to isolate the desired frequency range. The element-wise multiplication of the transmitted and received chirp signals is a valid method for obtaining the IF signal in certain situations, such as when the transmission medium is linear and time-invariant. However, in more complex scenarios, other methods may be required, such as correlation-based techniques. Regarding the phase unwrapping process, it is necessary when the phase values are outside the -π to +π range. The arctangent function used to calculate the phase values produces a discontinuity at ±π, resulting in phase jumps when the phase values cross this boundary. Phase unwrapping is a technique used to remove these jumps and obtain a continuous phase signal. Matlab has built-in functions such as 'unwrap' and 'angle' that can be used for phase unwrapping.
Why do we measure phase changes over 2 CHIRP cycles and not on the phase difference of the transmission signal to the phase of the received signal? It doesn't make sense, we are testing 2 transmission signals regardless of the components of the surrounding objects
The reason we measure phase changes over 2 CHIRP cycles in radar signal processing is to increase the accuracy and resolution of the measurements. When a radar transmits a CHIRP signal, the signal is modulated with a linearly increasing frequency over time. As the signal propagates through the environment and interacts with objects in its path, the signal is reflected back to the radar receiver, causing a phase shift in the received signal. To accurately measure the phase shift caused by the object, we need to compare the phase of the received signal to the phase of the transmitted signal. However, since the transmitted signal is modulated over time, the phase of the transmitted signal changes continuously. Therefore, a single measurement of the phase difference between the transmitted and received signals may not provide an accurate estimate of the object's position or velocity. By measuring the phase change over multiple CHIRP cycles, we can average out any errors or noise in the measurements and obtain a more accurate estimate of the object's position and velocity. This technique is called phase coherence, and it is commonly used in radar signal processing to improve the accuracy and resolution of the measurements. So, in summary, we measure phase changes over 2 CHIRP cycles in radar signal processing to increase the accuracy and resolution of the measurements, and to account for the modulation of the transmitted signal over time.
