Math 2.0

Information and communication theory, circuits Definition

Ambiguity function

Builds on Lp spaceShort-time Fourier transform

Definition

Let f∈L2(ℝ)f \in L^2(\R) (see Lp space). The ambiguity function of ff is the function Af ⁣:ℝ2→ℂAf \colon \R^2 \to \C, Af(x,ω)=∫ℝf ⁣(t+x2)f ⁣(t−x2)‾ e−2πiωt dt,Af(x, \omega) = \int_{\R} f\!\left(t + \tfrac{x}{2}\right) \overline{f\!\left(t - \tfrac{x}{2}\right)} \, e^{-2\pi i \omega t} \, dt, for a time shift x∈ℝx \in \R and a frequency shift ω∈ℝ\omega \in \R.

Remarks

The substitution t=s−x/2t = s - x/2 gives Af(x,ω)=eπixωVff(x,ω)Af(x, \omega) = e^{\pi i x \omega} V_f f(x, \omega), where VffV_f f is the short-time Fourier transform of ff with window ff. Hence ∣Af(x,ω)∣≤Af(0,0)=∥f∥22\abs{Af(x, \omega)} \le Af(0, 0) = \norm{f}_2^2, by the Cauchy–Schwarz inequality. In radar texts the ambiguity function is often written as χ(τ,ν)=∫s(t)s(t−τ)‾e2πiνt dt\chi(\tau, \nu) = \int s(t) \overline{s(t - \tau)} e^{2\pi i \nu t} \, dt. It differs from AfAf by a sign convention and a phase factor, and ∣χ(τ,ν)∣=∣Af(τ,−ν)∣\abs{\chi(\tau, \nu)} = \abs{Af(\tau, -\nu)} for s=fs = f.

Example: let f(t)=21/4e−πt2f(t) = 2^{1/4} e^{-\pi t^2}. Then f(t+x/2)f(t−x/2)‾=2 e−πx2/2e−2πt2f(t + x/2) \overline{f(t - x/2)} = \sqrt2 \, e^{-\pi x^2/2} e^{-2\pi t^2}, and the Fourier transform of e−2πt2e^{-2\pi t^2} is 2−1/2e−πω2/22^{-1/2} e^{-\pi \omega^2/2}. So Af(x,ω)=e−π(x2+ω2)/2Af(x, \omega) = e^{-\pi (x^2 + \omega^2)/2}, a single peak of height 1=∥f∥221 = \norm{f}_2^2 at the origin.

Non-example: the autocorrelation R(x)=∫ℝf(t)f(t−x)‾ dtR(x) = \int_\R f(t) \overline{f(t - x)} \, dt is not the ambiguity function. The substitution t=s+x/2t = s + x/2 shows R(x)=Af(x,0)R(x) = Af(x, 0), so RR is only the slice ω=0\omega = 0 of AfAf and does not see frequency shifts.

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  1. Lp space concept
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Further reading

  1. Web https://en.wikipedia.org/wiki/Ambiguity_function
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MSC94A12, 42A38
DefinesAmbiguity function
UsesLp space, Short-time Fourier transform

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