The theory behind sweep-sine measurements of LTI systems requires a signal with constantly changing the frequency. You cannot simply playback few tones - the whole frequency range is necessary.
So that if you want to identify your system with the impulse response $h[n]$, you feed the sweep sine signal $s[n]$ into it and record the output. Obviously output will be given by the convolution:
$$y[n]=h[n]\star s[n]$$
In order to obtain the impulse response of the system, it is required to convolve the output $y[n]$ with the inverse filter $f[n]$. Generally, the inverse filter is a sweep signal, inverted in time and with scaled amplitude. So in the end:
$$h[n]=y[n]\star f[n]$$
There are two major types of sweep signals: linear and logarithmic (exponential) frequency change. The latter one is more commonly used, since its spectrum is similar to a pink noise. Personally I always use the logarithmic sweep sine:
$$s(t) = \sin\left[ \dfrac{2\pi f_1 T}{\ln\left( \dfrac{2\pi f_2}{2\pi f_1} \right)}\left(e^{\dfrac{t}{T}\ln\left(\dfrac{2 \pi f_2}{2\pi f_1} \right)} -1\right) \right]$$
where:
$f_1$,$f_2$ - initial and final frequency of a sweep
$T$ - sweep duration in seconds
There is no strict rule on what should be the length of a sweep. For example in acoustics, the rule of thumb is that it should be at least as long as predicted reverberation time.
For more literature on the topic, please refer to the following sources:
Meng Q., et al. - Impulse Response Measurement With Sine Sweeps and
Amplitude Modulation
Schemes
Farina A. - Advancements in impulse response measurements by sine
sweeps
Farina A. - Simultaneous Measurement of Impulse Response and Distortion with a Swept-Sine Technique